{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 前言\n",
    "\n",
    "**价量相关性的平均数因子**：平均数因子利用成交量的信息，修正了传统 反转因子对股票价格涨跌的判断，即价格涨跌的反转不完全由价格自己 决定，还需看成交量的信息，若有量的确认，则月度行情的反转效应更强；若没有量的确认，则月度行情更容易呈现动量效应。\n",
    "\n",
    "**价量相关性的波动性因子**：波动性因子则从价量形态稳定性的角度，对 反转因子进行了改进，即无论股票价格过去的涨跌，只要每日价量关系 维持某种稳定形态，下个月就更有可能上涨；而价量关系在多种形态间频繁切换的股票，下个月更有可能下跌。\n",
    "\n",
    "**价量相关性的趋势因子**：股票价量相关性的变化趋势中也包含了有效的 选股信号。回测结果显示，价量相关系数随时间推移变小的股票，下个月的收益倾向于越高。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "code_folding": [
     0
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   "outputs": [],
   "source": [
    "# 引入库\n",
    "import sys\n",
    "\n",
    "sys.path.append('../..')\n",
    "\n",
    "from Hugos_tools.Tdays import (Tdaysoffset, get_trade_period)\n",
    "from Hugos_tools.BuildStockPool import Filter_Stocks\n",
    "from Hugos_tools.Stragegy_performance import (get_performance_table,\n",
    "                                              get_information_table,\n",
    "                                              calc_mono_score)\n",
    "import functools\n",
    "import warnings\n",
    "from typing import (List, Tuple, Dict, Callable, Union)\n",
    "from tqdm import tqdm_notebook\n",
    "\n",
    "import alphalens as al\n",
    "import alphalens.performance as perf\n",
    "import statsmodels.api as sm\n",
    "from scipy.stats import pearsonr\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import empyrical as ep\n",
    "\n",
    "from jqdata import *\n",
    "from jqfactor import (calc_factors, Factor)\n",
    "\n",
    "import seaborn as sns\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']  #用来正常显示中文标签\n",
    "plt.rcParams['axes.unicode_minus'] = False  #用来正常显示负号"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 价量相关性因子的构建\n",
    "\n",
    "经过探索，我们找到一种提炼有效信息的方案，以全体A股为研究样本（剔除其中的ST股、停牌股以及上市不足60个交易日的次新股），以 2014/01/01-2021/11/30为回测时间段，实施以下操作： \n",
    "1. 每月月底，回溯每只股票过去 20 个交易日的价量信息，每日计算该股票分钟收盘价与分钟成交量的相关系数； \n",
    "2. 每只股票取 20 日相关系数的平均值，做横截面市值中性化处理，将得到的结果记为平均数因子 PV_corr_avg； \n",
    "3. 每只股票取 20 日相关系数的标准差，同样做市值中性化处理，将结果记为波动性因子 PV_corr_std； \n",
    "4. 采用最简单的方式综合上述两个因子的信息，将 PV_corr_avg 和 PV_corr_std分别横截面标准化，等权线性相加得到价量相关性综合因子 PV_corr，即\n",
    "\n",
    "$$PV\\_corr = \\frac{PV\\_corr\\_avg-mean(PV\\_corr\\_avg)}{std(PV\\_corr_avg)}+\\frac{PV\\_corr\\_std-mean(PV\\_corr\\_std)}{std(PV\\_corr\\_std)}$$\n",
    "\n",
    "## 价量相关性因子的逻辑\n",
    "\n",
    "### 平均数因子\n",
    "\n",
    "先来看平均数因子 PV_corr_avg，它衡量了股票过去 20 日价量相关性的平均水平， 回测结果显示，**价量相关系数越小的股票，未来收益倾向于越高。**经过反复推敲，我们认为该因子其实是对传统反转因子做了修正。入下图，传统反转因子认为，股票的月度行情存在反转效应，过去 20 日上涨的股票下个月更倾向于下跌，应该归于空头； 而过去 20 日下跌的股票未来更有可能上涨，下个月应该归为多头。**价量相关性的平均数因子 PV_corr_avg 则加入量的信息，细化了反转因子对股票价格形态的分类。**\n",
    "![avatar]()\n",
    "\n",
    "对于价格上涨，可以进一步分为放量上涨和缩量上涨，前者的价量相关系数较大， 后者的价量相关系数较小，在 PV_corr_avg 因子看来，两者不可混为一谈。过去放量上 涨的股票，就好比武侠小说中的“末路英雄”，强弩之末，难穿鲁缟，耗尽了内力，下 个月便倾向于下跌，这一点与反转因子一致；而过去缩量上涨的股票，好比有绵绵内力 不断缓缓释放，上个月还未涨到尽头，仍有力量支撑，下个月便能延续之前的行情，继续上涨，这一点正好与反转因子相反。\n",
    "\n",
    "对于价格下跌，也可以进一步分为放量下跌和缩量下跌，前者的价量相关系数小， 后者的价量相关系数大，PV_corr_avg 因子对这两类股票也持有不同的态度。放量下跌 的股票，PV_corr_avg 的判断与反转因子一致，认为下个月行情更容易反转，归为多头； 而过去平均来看缩量下跌的股票，由于还未经历放量见底的过程，下个月的反转行情相对较弱，仍然归于空头，这一点与反转因子不同。\n",
    "\n",
    "综上所述，平均数因子 PV_corr_avg 对传统反转因子的修正逻辑可总结为：**价格涨跌的反转不完全由价格自己决定，还需看成交量的信息，若有量的确认，则月度行情的反转效应更强；若没有量的确认，则月度行情的动量效应更强。**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 波动性因子\n",
    "\n",
    "再来看衡量股票过去价量相关性波动情况的 PV_corr_std 因子，回测结果显示，因 子值越小，股票未来收益越高。我们也分 4 种价量关系分析该因子的选股逻辑。 \n",
    "\n",
    "对于缩量上涨和放量下跌的情形，若股票的价量相关系数波动较小，则意味着股票在过去 20 个交易日，每日都稳定呈现缩量上涨或放量下跌的形态，自然与 PV_corr_avg因子的判断一致，将股票归为多头。\n",
    "\n",
    "而对另外两种情形的分析，PV_corr_std因子则与PV_corr_avg不同。对于放量上涨， 若价量相关系数波动较小，则意味着股票过去 20 个交易日，每日都呈现放量上涨的状 态，此时它不再是“末路英雄”，而是“绝顶高手”，比如受到了众多利好信息的持续刺 激，这类股票下个月应该仍然归为多头，期待上涨行情得以延续；对于缩量下跌，若股 票每日都稳定呈现此状态，则 PV_corr_std 因子对该股的判断与反转因子相同，认为下个月更有可能反转，出现上涨行情。\n",
    "\n",
    "其实，**波动性因子 PV_corr_std 包含的选股信息也可以看做是对反转因子的一种修 正：无论股票过去是上涨还是下跌，只要每日价量关系维持一种稳定的形态， PV_corr_std 因子就把这只股票归为未来的多头；而价量关系在多种形态间频繁转换的股票，就会被 PV_corr_std 因子归为空头。**\n",
    "\n",
    "![avatar]()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**小结**\n",
    "\n",
    "总结了前两部分的分析，价量相关性因子可以看做是对传统反转的修正。\n",
    "![avatar]()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "由上，pv_corr可以看作是对传统反转因子的修正，价量相关性因子的选股信息必然与传统反转存在重叠。我们可进一步精炼选股信息，先**将两个子因子PV_corr_avg和PV_corr_std 分别剔除反转因子，再各自横截面标准化，等权线性相加构建综合因子，将得到的新因子记为 PV_corr_deRet20。**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 趋势因子的增量信息\n",
    "\n",
    "在前文研究的基础上，我们额外发现股票价量相关性的变化趋势也能带来一些增量 信息，因此本节内容做进一步探索，挖掘新信息，并在最后呈现包含价量相关性3个维度信息的最终因子。\n",
    "\n",
    "## 价量相关性的趋势因子\n",
    "\n",
    "本节介绍的选股因子计算过程如下： \n",
    "1. 每月月底，仍然回溯每只股票过去 20 个交易日的价量信息，每日计算该股票分钟收盘价与分钟成交量的相关系数； \n",
    "2. 将每只股票的 20 个相关系数𝜌𝑡对时间𝑡回归，取回归系数𝛽，即𝜌𝑡 = 𝛽 ∗ 𝑡 + 𝜀𝑡，其中，𝑡取值为 1,2,3,……,20； \n",
    "3. 将所有股票的回归系数𝛽在横截面上剔除市值、传统价量类因子（20 日反转、20 日换手率、20 日波动率因子），将得到的结果定义为趋势因子 PV_corr_trend。\n",
    "\n",
    "## 最终的价量相关性因子——CPV\n",
    "\n",
    "经检验，上一小节介绍的趋势因子 PV_corr_trend 在剔除原来的综合因子 PV_corr_deRet20 后，仍然具有一定的选股能力，因此我们将 PV_corr_trend 带来的增量 信息叠加到 PV_corr_deRet20 之上，最终因子命名为CPV因子（Correlation of Price and Volume），涵盖了本篇报告提出的价量相关性 3 个维度上的综合信息：\n",
    "\n",
    "$$CPV = \\frac{PV\\_corr\\_deRet20+mean(PV\\_corr\\_deRet20)}{std(PV\\_corr\\_deRet20)} + \\frac{PV\\_corr\\_trend-mean(PV\\_corr\\_trend)}{std(PV\\_corr\\_trend)}$$\n",
    "\n",
    "![avatar]()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "code_folding": [
     4,
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   },
   "outputs": [],
   "source": [
    "\"\"\"因子构建相关\"\"\"\n",
    "# 修饰器-分钟及数据数量大用次部分进行拆分\n",
    "\n",
    "\n",
    "def split_securities(Limit: int = 500):\n",
    "    def decorator(func: Callable):\n",
    "        @functools.wraps(func)\n",
    "        def wrapper(*args, **kw):\n",
    "\n",
    "            if 'securities' not in kw:\n",
    "\n",
    "                securities = args[0]\n",
    "\n",
    "                args = args[1:]\n",
    "\n",
    "            else:\n",
    "\n",
    "                securities = kw['securities']\n",
    "\n",
    "                del kw['securities']\n",
    "\n",
    "            if isinstance(securities, str):\n",
    "\n",
    "                securities = [securities]\n",
    "\n",
    "            size = len(securities)\n",
    "\n",
    "            if size > Limit:\n",
    "\n",
    "                return pd.concat((func(securities[i:i + Limit], *args, **kw)\n",
    "                                  for i in range(0, size, Limit)))\n",
    "\n",
    "            else:\n",
    "\n",
    "                return func(securities, *args, **kw)\n",
    "\n",
    "        return wrapper\n",
    "\n",
    "    return decorator\n",
    "\n",
    "# 获取日内数据\n",
    "\n",
    "\n",
    "@split_securities()\n",
    "def get_intraday_price(securities: Union[str, List], end_date: str,\n",
    "                       count: int) -> pd.DataFrame:\n",
    "    \"\"\"获取日内分钟数据\n",
    "\n",
    "    Args:\n",
    "        securities (Union[str, List]): 标的\n",
    "        end_date (str): 观察日\n",
    "        count (int): 天数\n",
    "\n",
    "    Returns:\n",
    "        pd.DataFrame: 数据\n",
    "    \"\"\"\n",
    "    return get_price(securities,\n",
    "                     end_date=end_date + ' 15:00:00',\n",
    "                     count=240 * count,\n",
    "                     frequency='1m',\n",
    "                     fields=['close', 'volume'],\n",
    "                     panel=False)\n",
    "\n",
    "\n",
    "# 计算相关系数\n",
    "def calc_corr(price: pd.DataFrame) -> pd.Series:\n",
    "    \"\"\"计算量价相关系数\n",
    "\n",
    "    Args:\n",
    "        price (pd.DataFrame): 量价数据，index-datetime\n",
    "\n",
    "    Returns:\n",
    "        pd.Series: 相关系数\n",
    "    \"\"\"\n",
    "    group = price.index.normalize()\n",
    "\n",
    "    return price.groupby(price.index.normalize()).apply(\n",
    "        lambda x: pearsonr(x['close'], x['volume'])[0])\n",
    "\n",
    "\n",
    "# 计算标准分\n",
    "def scaling_z_score(ser: pd.Series) -> pd.Series:\n",
    "    \"\"\"标准分\n",
    "\n",
    "    Args:\n",
    "        ser (pd.Series): 因子值\n",
    "\n",
    "    Returns:\n",
    "        pd.Series: 标准化后的因子\n",
    "    \"\"\"\n",
    "    return (ser - ser.mean()) / ser.std()\n",
    "\n",
    "\n",
    "# 计算残差\n",
    "def calc_ols(x: pd.Series, y: pd.Series,\n",
    "             method: str = 'resid') -> pd.Series:\n",
    "    \"\"\"计算回归\n",
    "\n",
    "    Args:\n",
    "        x (pd.Series): 自变量\n",
    "        y (pd.Series): 应变量\n",
    "\n",
    "    Returns:\n",
    "        pd.Series: 残差\n",
    "    \"\"\"\n",
    "\n",
    "    result = sm.OLS(y.fillna(0), sm.add_constant(np.nan_to_num(x))).fit()\n",
    "\n",
    "    return getattr(result, method)\n",
    "\n",
    "\n",
    "def Culling_factor(factor_ser: pd.Series,\n",
    "                   other_factor: Union[pd.Series, pd.DataFrame],\n",
    "                   scaling: bool = True) -> pd.Series:\n",
    "    \"\"\"计算剔除其他因子\n",
    "\n",
    "    再各自横截面标准化，等权线性相加构建综合因子\n",
    "    Args:\n",
    "        factor_ser (pd.Series): 因子\n",
    "        other_factor (pd.Series|pd.DataFrame): 反转因子\n",
    "        scaling (bool):是否标准化\n",
    "    Returns:\n",
    "        pd.DataFrame: 结果\n",
    "    \"\"\"\n",
    "\n",
    "    # 去除反转因子的影响\n",
    "    ser = calc_ols(other_factor, factor_ser, 'resid')\n",
    "\n",
    "    if scaling:\n",
    "        # 标准化\n",
    "        scaling_ser = scaling_z_score(ser)\n",
    "\n",
    "    else:\n",
    "\n",
    "        scaling_ser = ser\n",
    "\n",
    "    return scaling_ser\n",
    "\n",
    "\n",
    "@split_securities()\n",
    "def calc_pv_corr(securities: Union[list, str], end_date: str, count: int,\n",
    "                 market_cap: pd.Series) -> pd.DataFrame:\n",
    "    \"\"\"计算因子\n",
    "\n",
    "    Args:\n",
    "        securities (Union[list, str]): 标的\n",
    "        end_date (str): 观察日\n",
    "        count (int): 周期\n",
    "        market_cap (pd.Series): 市值数据\n",
    "\n",
    "    Returns:\n",
    "        pd.DataFrame: 因子\n",
    "    \"\"\"\n",
    "    # 获取分钟数据\n",
    "    price = get_intraday_price(securities, end_date=end_date, count=count)\n",
    "    # 获取量价相关系数\n",
    "    pv_corr = (price.set_index('time').groupby('code').apply(calc_corr).T)\n",
    "\n",
    "    # 计算pv_corr_trend所需的回归系数\n",
    "\n",
    "    pv_beta = pv_corr.apply(lambda x: calc_ols(np.arange(1,\n",
    "                                                         len(x) + 1), x,\n",
    "                                               'params')[1])  # 这里只是中间过程\n",
    "\n",
    "    # 平均数因子\n",
    "    pv_corr_avg = pv_corr.mean()\n",
    "    # 波 动性因子\n",
    "    pv_corr_std = pv_corr.std()\n",
    "\n",
    "    # 市值-标准化处理\n",
    "    market_cap = scaling_z_score(market_cap.loc[securities])\n",
    "    # 市值中性化\n",
    "    pv_corr_avg = Culling_factor(pv_corr_avg, market_cap, False)\n",
    "    pv_corr_std = Culling_factor(pv_corr_std, market_cap, False)\n",
    "    pv_beta = Culling_factor(pv_beta, market_cap, False)\n",
    "\n",
    "    pv_corr = scaling_z_score(pv_corr_avg) + scaling_z_score(pv_corr_std)\n",
    "\n",
    "    df = pd.concat((pv_corr_avg, pv_corr_std, pv_corr, pv_beta), axis=1)\n",
    "    df.columns = ['pv_corr_avg', 'pv_corr_std', 'pv_corr', 'pv_corr_trend']\n",
    "\n",
    "    return df\n",
    "\n",
    "\n",
    "class PV_corr(Factor):\n",
    "\n",
    "    warnings.filterwarnings(\"ignore\")\n",
    "    name = 'PV_corr'\n",
    "    max_window = 20  # 可做敏感分析\n",
    "    # ROC20-20日动量\n",
    "    # VOL20-20日换手率\n",
    "    # 聚宽居然木有波动率....\n",
    "    dependencies = ['market_cap', 'ROC20', 'VOL20', 'close']\n",
    "\n",
    "    def calc(self, data: Dict) -> pd.Series:\n",
    "\n",
    "        codes = data['market_cap'].columns.tolist()\n",
    "        tradeDate = data['market_cap'].index[-1].strftime('%Y-%m-%d')\n",
    "        market_cap = data['market_cap'].iloc[-1]\n",
    "\n",
    "        # 获取反转因子\n",
    "        volatility: pd.Series = data['close'].pct_change().std()  # 计算20日波动率\n",
    "        roc: pd.Series = data['ROC20'].iloc[-1]\n",
    "        vol: pd.Series = data['VOL20'].iloc[-1]\n",
    "        other_factor: pd.DataFrame = pd.concat((roc, vol, volatility), axis=1)\n",
    "        # 反转因子标准化\n",
    "        other_factor = other_factor.apply(scaling_z_score)\n",
    "\n",
    "        df = calc_pv_corr(securities=codes,\n",
    "                          end_date=tradeDate,\n",
    "                          count=self.max_window,\n",
    "                          market_cap=market_cap)\n",
    "\n",
    "        # 计算pv_corr_deret20\n",
    "        pv_corr_avg_: pd.Series = Culling_factor(df['pv_corr_avg'],\n",
    "                                                 other_factor, True)\n",
    "\n",
    "        pv_corr_std_: pd.Series = Culling_factor(df['pv_corr_std'],\n",
    "                                                 other_factor, True)\n",
    "\n",
    "        df['pv_corr_deret20'] = pv_corr_avg_ + pv_corr_std_\n",
    "\n",
    "        # 计算pv_corr_trend\n",
    "        df['pv_corr_trend'] = Culling_factor(df['pv_corr_trend'], other_factor,\n",
    "                                             False)\n",
    "\n",
    "        df['CPV'] = scaling_z_score(df['pv_corr_deret20']) + scaling_z_score(\n",
    "            df['pv_corr_trend'])\n",
    "\n",
    "        self.market_cap: pd.Series = market_cap\n",
    "        self.other_factor: pd.DataFrame = other_factor\n",
    "        self.pv_corr_factor: pd.DataFrame = df\n",
    "\n",
    "\n",
    "\"\"\"因子获取\"\"\"\n",
    "\n",
    "\n",
    "def get_factor(symbol: str, tradeDt) -> pd.DataFrame:\n",
    "    \"\"\"获取因子\n",
    "\n",
    "    Args:\n",
    "        symbol (str): 股票池范围 A为全A\n",
    "        startDate (str): 起始日期\n",
    "        endDate (str): 结束日期\n",
    "        freq (str): 频率\n",
    "\n",
    "    Returns:\n",
    "        pd.DataFrame: 因子\n",
    "    \"\"\"\n",
    "\n",
    "    for tradeDt in tqdm_notebook(periods, desc='因子获取'):\n",
    "\n",
    "        stock_pool_func = Filter_Stocks(symbol, tradeDt)\n",
    "        stock_pool_func.filter_paused(21, 20)  # 过滤21日停牌超过20日的股票\n",
    "        stock_pool_func.filter_st()  # 过滤st\n",
    "        stock_pool_func.filter_ipodate(60)  # 过滤次新\n",
    "\n",
    "        PV_CORR = PV_corr()\n",
    "        codes = stock_pool_func.securities\n",
    "        calc_factors(codes, [PV_CORR], start_date=tradeDt, end_date=tradeDt)\n",
    "        yield PV_CORR.pv_corr_factor\n",
    "\n",
    "\n",
    "def get_freq_price(security: Union[List, str], periods: List) -> pd.DataFrame:\n",
    "    \"\"\"获取对应频率价格数据\n",
    "\n",
    "    Args:\n",
    "        security (Union[List, str]): 标的\n",
    "        periods (List): 频率\n",
    "\n",
    "    Yields:\n",
    "        Iterator[pd.DataFrame]\n",
    "    \"\"\"\n",
    "    for trade in tqdm_notebook(periods, desc='获取收盘价数据'):\n",
    "\n",
    "        yield get_price(security,\n",
    "                        end_date=trade,\n",
    "                        count=1,\n",
    "                        fields='close',\n",
    "                        fq='post',\n",
    "                        panel=False)\n",
    "\n",
    "\n",
    "def get_pricing(factor_df: pd.DataFrame, last_periods: str = None) -> pd.DataFrame:\n",
    "    \"\"\"获取价格数据\n",
    "\n",
    "    Args:\n",
    "        factor_df (pd.DataFrame): 因子数据  MultiIndex levels-0 date levels-1 code\n",
    "        last_periods (str, optional): 最后一期数据. Defaults to None.\n",
    "\n",
    "    Returns:\n",
    "        pd.DataFrame\n",
    "    \"\"\"\n",
    "    if last_periods is not None:\n",
    "        periods = factor_df.index.levels[0].tolist(\n",
    "        ) + [pd.to_datetime(last_periods)]\n",
    "    else:\n",
    "        periods = factor_df.index.levels[0]\n",
    "\n",
    "    securities = factor_df.index.levels[1].tolist()\n",
    "\n",
    "    # 获取收盘价\n",
    "    price_list = list(get_freq_price(securities, periods))\n",
    "    price_df = pd.concat(price_list)\n",
    "    pivot_price = pd.pivot_table(price_df,\n",
    "                                 index='time',\n",
    "                                 columns='code',\n",
    "                                 values='close')\n",
    "    return pivot_price\n",
    "\n",
    "\n",
    "class get_factor_returns(object):\n",
    "\n",
    "    def __init__(self, factors: pd.DataFrame, factor_name: str, max_loss: float) -> None:\n",
    "        '''\n",
    "        输入:factors MuliIndex level0-date level1-asset columns-factors\n",
    "        '''\n",
    "        self.factors = factors\n",
    "        self.factor_name = factor_name\n",
    "        self.name = self.factor_name\n",
    "        self.max_loss = max_loss\n",
    "\n",
    "    def get_calc(self, pricing: pd.DataFrame, periods: Tuple = (1,), quantiles: int = 5) -> pd.DataFrame:\n",
    "\n",
    "        factor_ser: pd.Series = self.factors[self.factor_name]\n",
    "        preprocessing_factor = al.utils.get_clean_factor_and_forward_returns(factor_ser,\n",
    "                                                                             pricing,\n",
    "                                                                             periods=periods,\n",
    "                                                                             quantiles=quantiles,\n",
    "                                                                             max_loss=self.max_loss)\n",
    "\n",
    "        # 预处理好的因子\n",
    "        self.factors_frame = preprocessing_factor\n",
    "\n",
    "        # 分组收益\n",
    "        self.group_returns = pd.pivot_table(preprocessing_factor.reset_index(\n",
    "        ), index='date', columns='factor_quantile', values=1)\n",
    "\n",
    "        # 分组累计收益\n",
    "        self.group_cum_returns = ep.cum_returns(\n",
    "            self.group_returns)\n",
    "\n",
    "    def long_short(self, lower: int = 1, upper: int = 5) -> pd.Series:\n",
    "        '''\n",
    "        获取多空收益\n",
    "        默认地分组为1,高分组为5\n",
    "        '''\n",
    "        try:\n",
    "            self.group_returns\n",
    "        except NameError:\n",
    "            raise ValueError('请先执行get_calc')\n",
    "\n",
    "        self.long_short_returns = self.group_returns[upper] - \\\n",
    "            self.group_returns[lower]\n",
    "        self.long_short_returns.name = f'{self.name}_excess_ret'\n",
    "\n",
    "        self.long_short_cum = ep.cum_returns(self.long_short_returns)\n",
    "        self.long_short_cum.name = f'{self.name}_excess_cum'\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "code_folding": [
     0
    ],
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e53fda63455a4951bff1d40c201c6048",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, description='因子获取', max=94, style=ProgressStyle(description_width='initial…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "# 因子获取\n",
    "periods = get_trade_period('2014-01-01', '2021-10-31', 'ME')\n",
    "factor_dfs = list(get_factor('A', periods))\n",
    "\n",
    "# 因子值\n",
    "factor_df = pd.concat({tradeDt: df for tradeDt, df in zip(\n",
    "    periods, factor_dfs)}, names=['date', 'asset'])\n",
    "\n",
    "# 数据储存\n",
    "factor_df.to_csv('cpv.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "code_folding": [
     0
    ]
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "060d532ab1d24926bf5f0f9d5fd80ffe",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, description='获取收盘价数据', max=95, style=ProgressStyle(description_width='init…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "# 读取\n",
    "factor_df = pd.read_csv('cpv.csv',index_col=[0,1],parse_dates=['date'])\n",
    "\n",
    "# 获取收盘价数据\n",
    "pricing = get_pricing(factor_df, '2021-11-30')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>pv_corr_avg</th>\n",
       "      <th>pv_corr_std</th>\n",
       "      <th>pv_corr</th>\n",
       "      <th>pv_corr_trend</th>\n",
       "      <th>pv_corr_deret20</th>\n",
       "      <th>CPV</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th>asset</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">2021-10-29</th>\n",
       "      <th>688799.XSHG</th>\n",
       "      <td>-0.040364</td>\n",
       "      <td>-0.059105</td>\n",
       "      <td>-2.062111</td>\n",
       "      <td>0.003719</td>\n",
       "      <td>-1.530446</td>\n",
       "      <td>-0.588403</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>688800.XSHG</th>\n",
       "      <td>-0.044931</td>\n",
       "      <td>0.062279</td>\n",
       "      <td>0.593672</td>\n",
       "      <td>0.004973</td>\n",
       "      <td>-1.193098</td>\n",
       "      <td>-0.217781</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>688819.XSHG</th>\n",
       "      <td>0.022162</td>\n",
       "      <td>0.007419</td>\n",
       "      <td>0.567500</td>\n",
       "      <td>0.006496</td>\n",
       "      <td>0.947565</td>\n",
       "      <td>1.386607</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>688981.XSHG</th>\n",
       "      <td>-0.035503</td>\n",
       "      <td>-0.117590</td>\n",
       "      <td>-3.293693</td>\n",
       "      <td>-0.002650</td>\n",
       "      <td>-2.185112</td>\n",
       "      <td>-1.765053</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>689009.XSHG</th>\n",
       "      <td>-0.017115</td>\n",
       "      <td>0.057875</td>\n",
       "      <td>0.996562</td>\n",
       "      <td>-0.003718</td>\n",
       "      <td>0.413937</td>\n",
       "      <td>-0.155996</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        pv_corr_avg    ...          CPV\n",
       "date       asset                       ...             \n",
       "2021-10-29 688799.XSHG    -0.040364    ...    -0.588403\n",
       "           688800.XSHG    -0.044931    ...    -0.217781\n",
       "           688819.XSHG     0.022162    ...     1.386607\n",
       "           688981.XSHG    -0.035503    ...    -1.765053\n",
       "           689009.XSHG    -0.017115    ...    -0.155996\n",
       "\n",
       "[5 rows x 6 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 数据结构如下\n",
    "factor_df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "code_folding": [
     0
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x648 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 查看因子分布\n",
    "fig, axes = plt.subplots(2, 3, figsize=(18, 9))\n",
    "\n",
    "axes = [i for x in axes for i in x]\n",
    "for ax, (name, ser) in zip(axes, factor_df.items()):\n",
    "\n",
    "    ax.set_title(name)\n",
    "    ser.hist(ax=ax)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "code_folding": [
     0
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dropped 0.0% entries from factor data (0.0% after in forward returns computation and 0.0% in binning phase). Set max_loss=0 to see potentially suppressed Exceptions.\n",
      "Dropped 0.0% entries from factor data (0.0% after in forward returns computation and 0.0% in binning phase). Set max_loss=0 to see potentially suppressed Exceptions.\n",
      "Dropped 0.0% entries from factor data (0.0% after in forward returns computation and 0.0% in binning phase). Set max_loss=0 to see potentially suppressed Exceptions.\n",
      "Dropped 0.0% entries from factor data (0.0% after in forward returns computation and 0.0% in binning phase). Set max_loss=0 to see potentially suppressed Exceptions.\n",
      "Dropped 0.0% entries from factor data (0.0% after in forward returns computation and 0.0% in binning phase). Set max_loss=0 to see potentially suppressed Exceptions.\n",
      "Dropped 0.0% entries from factor data (0.0% after in forward returns computation and 0.0% in binning phase). Set max_loss=0 to see potentially suppressed Exceptions.\n"
     ]
    }
   ],
   "source": [
    "# 获取因子回测数据\n",
    "factor_name = factor_df.columns.tolist()\n",
    "res_dic = {}\n",
    "\n",
    "for ax, name in zip(axes, factor_name):\n",
    "\n",
    "    res = get_factor_returns(factor_df, name, 0.4)\n",
    "    res.get_calc(pricing)\n",
    "    res.long_short(5, 1)\n",
    "    res_dic[name] = res"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "code_folding": [
     0
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1368x648 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 因子分组收益\n",
    "fig, axes = plt.subplots(2, 3, figsize=(19, 9))\n",
    "axes = [i for x in axes for i in x]\n",
    "for ax,(k,v) in zip(axes,res_dic.items()):\n",
    "    v.group_cum_returns.plot(\n",
    "        ax=ax,\n",
    "        title=k,\n",
    "        color=['Navy', 'LightGrey', 'DimGray', 'DarkKhaki', 'LightSteelBlue'])\n",
    "    res.long_short_cum.plot(ax=ax, ls='--', color='red')\n",
    "\n",
    "plt.subplots_adjust(hspace=0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "code_folding": [
     0
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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617+y2Wab8dxzz7Hjjjtyww03cOmll/Lcc8+xbNkydtttNwCWLFnCgw8+yNZbb73Wvf/85z+z11578bWvfY0f/OAH1NXVNS1h3GmnnbjlllsAOO200zjttNPITC688EJ+/OMfN31zuT6rV6/m9NNP5+qrr25Te0mqhlqL6wC/+MUv+NnPfsa5557Lo48+ypAhQ9a619lnn83ZZ5/NNddcw+TJkznppJP41a9+xT333MNLL73U1G7ZsmXcc889XHTRRfzqV7/ivvvu48QTT/zA/waS1J5qMa5DKbE0atSotcYHpb2zzj777Pfdf4sttuChhx5i+fLlnHLKKXzxi1+kV69eANx99928/PLLjBo1qm1vegfboARLRFwOzKa0z8pOEdGb0gqWgcB8YDowgtLKlMOL88ZrBwHzMnN5RPSM0jtfh6R289nPfpYZM2bw1FNPsXTpUt5++22eeuopPvaxj7UYdFeuXMmMGTPo168f119/PXvttRcAJ554IrNnz+avf/0rQ4YMYcSIESxfvnytJYc33XQTO++8M//5n//JnDlz+PnPf87ixYub7v3888+z/fbbs+eee3LaaadRX1/Pb37zG6677jqWLFnSlATZY489moJ3uV/+8pccffTR3H///fzyl7/k3HPPbXoOtSURwaGHHsqNN97Y5vdrzJgxrW7uJUmdQS3H9Z49e7L//vszadKk9yVYGh111FEcfPDBbL/99jz++OPsvPPOvPvuu7z22msMHz6cI444gs997nNNE/OPf/zjJlgkVVWtxvUpU6Ywe/Zsfve7372v7tZbb+XnP/8555xzDq+99hq/+c1vuOmmmzjkkEOAUjJp55135v7772fUqFE8//zzXHzxxdx3333v20OmWjZ0BUs/YJvMfDciLqK0kW0P4Npiv5aJwISImEVpU9tTyq4dA5xbHE8F5gBt/y8hSet0zz338P3vf7/p/OWXX27KSAPcfPPNXH311fTp04cVK1Zw9tln89ZbbxER/PznP2f58uVNAbu5u+4q7V3d0pLDxizyr3/9a6677jpOP/10AM477zxOPfVU6uvrm9pmZtO3kgCvv/46m2+++fteb/bs2cycOZOf/exnfPrTn+b5559vuh7ghRde4MILL+T222/nlVdeaXoef8aMGU1LEUeOHMlPfvIT+vfv3+KYJk6cyIsvvvi+zRMlqbOo1bg+f/78pon8H/7wh6aNxxvjemY2PaN///33s9tuu3HCCSdwwgknALBgwQJOPfVU7rvvPq699tqmX7d444032Gyzzdr25ktSB6jVuP7UU0/xne98h2nTprHppps23aMxrj/11FNNZaeeeiqnnnoqe++9Nw0NDfTt25e33nqLRx55hNGjR7Ny5UqOPfZYJkyYwI477tjWt77DtTnBkpkTy47PLDueQemXhMrbvgOc3Mp9RpUdjwXGtr27ktbn0EMP5dBDD206L980q9xLL73E1KlTmTx5Ms888wyXXnopl156KQCnn356RVngOXPm8KEPfYhjjjkGYK17/e///i9nnnkmn/jEJ/jMZz4DwKJFi96358mjjz7KSSedxK233kqPHj3Yfffd2X333XnhhReagujq1auZP38+ABMmTODXv/41m2++Of379+faa68FSs+ltvYTcABnnXUWH/3oRxk2bBhQWm7ut5qSOpNajetf+cpXWLhwIRHBRz7ykaafMm2M65MnT+bmm29m6623ZvPNN3/fr1uUO/HEE7nnnnsYMmQIa9as4ac//ekGvxeSVKlajetjxozhH//4B5///OcBGDRoED/60Y/WOV9fuXIlhx56KHV1dbz99tucdNJJ1NfXc8UVVzB//ny+9rWvAbDZZpsxbdq0DX4/2kule7BI6qL+6Z/+iUceeYT+/fvz6KOPNpUff/zxzJkz532/yHPnnXdy2WWXNZ0PHz4cKGWXyzehAhg7diw9e/bkoosu4t577+Wb3/wmUNqgav/99+f4449nzJgxQGkCPXXqVC6++OKm61etWsUFF1zApEmTmjbceu211zjggAN48803m36GbY899uDJJ58E4JJLLllro65GjfWNTj311LXO33rrrVbfo+ZtJakz625x/Y477mhxnI313/zmN5v60ZIBAwbwwAMPAKXn97v7SsWI2Ba4HXggMy8rKz8Y+HZZ0/8HOALYFJgMPF+UH5uZC4u9EgcAF2TmjIg4DPhY8cWopI2ou8X13/72ty2Os/l8HUqrzBvNmTPnffWtzf2rLcp/G7szq6+vz/JdidU2Ay65q2qvveCKEVV77VoQEXSV//2WW7NmTdNPza1LZnaaZynXpT3+HSLi8cysX3/L9tMZJuKVxPVqxjYwvqnjdMXYblxv8R4bNa5HRA/gD8DTwJLyuN5CuznApyntl7h3Zn6rrH4g8A3gu8D3MvPEiLgTOC4zV66vH5XO1523qjsyrlffxozrrmBRt+QHdOfVlmANdIlg3VUVE+yplCbia8nMeyltUF4+EX+M0kT8+hYm4q8CXwW+B8wAzgGO6+AhSOpEjOvVl5mrI+JoSrF6wDqajgCmZeY7EdGL0i+ClusNLKK0h2KfiBgOzGpLckVS92Fc33Bte+ckSd1GZq4GjgZmradp00QccCIuSZ1YZja0odlpwA1l52dExMyIuCYitgAWA3sCewELgQuApRFxd0R0jt9AlaROzASLJNUgJ+KSVFsiYgdg58z8E0BmTsjMjwFDgXeBr2bmfKABGAc8DjwJHA+MBM5r5b6jI2J2RMxuaGjLR4skdV818YiQj4tI0gfT0kQcmBCltaA/oTQR/35ENE7EbwF2oDQRP4TSY0a3tnDf0cBogF133XVjDEWSVHIK8KvmhZmZEXEPcFJxfj5AscfWGcDgzFwVEWtaumlmjgfGQ2kPlg7qe7fmf6tI3YcrWCRJLWl1Ig7cA3y0OD8/M/cDhgNXF01WAa1OxDOzPjPrm//UnySp/UTE5RFxZFnRWnE9IrYvqxsG/LmsbhAwLzOXAz2L5HpdB3dZkro8EyySJCfiktT99AO2AYiIIcD8zHylrP60iHg8ImZS2hj3p2V1Y4CriuOplDY8n9LhPZakLq4mHhGSuqP+/fu7c3cn0L9//2p3ob20ZSJ+DPAW8AKlZeONxgDnFseNE/EbO7zHUjdkbK++rhzXM3Ni2fGZZcczgSOatb0CuKKV+4wqOx4LjG3vvkq1wrhefRszrptgkbqoBQsWVLsL6uKciEudj7FdkroX43pt8REhSZIkSZKkCrmCRepGqrkLPbgTvSRJkqTa5QoWSZIkSZKkCplgkSRJkiRJqlCbHhGKiG2B24EHMvOyVtr8FpiVmZdFRA/gOmAv4EXgS5n5VkRMofQzcBdk5oyIOAz4WLEpoiRJWo9qPgroY4CSJEmtW+8KliJZMhWYu442J7J2suZYYEVm7gPMA06PiIHAq8DRwFlFu3OAcRvWdUmSJEmSpM5hvQmWzFxNKSkyq6X6iOgFnADcVFY8HGj8iu1O4ECgN7AIeAnoExHDKa14WbnBvZckSZIkSeoE2rQHS2Y2rKP6h8C3gTVlZf2AZcVxQ3G+GNiT0mNDC4ELgKURcXdEjPqA/ZYkSZIkSeo0KtrkNiI+C7yRmY83q+oJRGMzoC4z51NKtowDHgeeBI4HRgLntXL/0RExOyJmNzSsK8cjSZIkSZJUPW3a5HYdvgh8ISKOBbYANo2ITYCllB4JAugDLAHIzPMBis1uzwAGZ+aqiFjzvjuX2o8HxgPU19dnhX2VJEmSJEnqEBu0giUiLo+IIzPz7MzcPjN3AC4EfpSZ3wamA40/NXB4cd547SBgXmYuB3pGRAB1FY1CkiRJkiSpijb0EaF+wDbrqJ8I9IqIWcBA4JqyujHAVcXxVGAOMGUD+yFJkiRJklR1bX5EKDMnlh2fuZ76d4CTW7nPqLLjscDYtvZBkiRJkiSpM6pok1tJkiRJkiSZYJEkSZIkSaqYCRZJkiSpi4uIbSPigYi4rIW6aRExKyIeioh/K8p6RMQNEfFIREyOiM2L8ikR8UREDCvOD4uIizfqYCSpizLBIkk1yIm4JHUfEdGD0o9HzG2lSS9gWGYOzczvFmXHAisycx9gHnB6RAwEXgWOBs4q2p0DjOuwzktSN2KCRZJqjBNxSepeMnM1pVg8q5UmPYofoSg3HLirOL4TOBDoDSwCXgL6RMRwYFZmrmz/XktS92OCRZJqjBNxSep+MrNhHdV1xarFByLiwKKsH7CsOG4ozhcDewJ7AQuBC4ClEXF3RIxqflNJ0tra/DPNkqTuIzMbIqK16rqIeKA4/m5mTqPtE/GpEXE3MCEzb+2g7kuSPoDMHAgQEbsBDxYrEHsCjR8EAdRl5vyIaKC0EvEWYAfgeOAQ4F7gfXE9IkYDowF23XXXDh6JupMBl9y1/kYdaMEVI6r6+uqeXMEiSVpLZg7MzP2BLwMTI2JLWpmIU0q2jAMeB56kNBEfCZzX0r0jYnREzI6I2Q0N6/qyVZLU3oq4vQjYGVhKaSUiQB9gSdHm/Mzcj9LKxatLRbkKWNPKPcdnZn1m1vft27ejhyBJnZoJFklSi5yIS1LXFRGXR8SREbF5RHyoKOsLbA+8CEwHGr/CP7w4b7x2EDAvM5cDPaO05LFuow5AkrogEyySJCfiktT99AO2Kf6mRcTDlPbQOi8z3wYmAr0iYhYwELim7NoxwFXF8VRgDjBlI/Vbkros92CRJMHaE/G7I+IdYFOKiXhETAQmFBPxl4BTyq4dA5xbHDdOxG/cWB2XJJVk5sSy4zPLqvZuoe07wMmt3GdU2fFYYGz79VKSui8TLJJUo5yIS5IkSe3HBIskSer0qvlrE/7ShCRJagv3YJEkSZIkSapQmxIsEbFtRDwQEZc1K6+LiJ9ExMMR8UREDC/Ke0TEDRHxSERMjojNi/IpRbthxflhEXFxO49JkiRJkiRpo1pvgiUielDatHBu87ripzh/m5mDgeOAHxdVxwIrMnMfYB5wekQMBF4FjgbOKtqdA4yrdBCSJEmSJEnVtN4ES2auppQUmdVK/T3F4SJg2+J4OND4sPSdwIFA76LNS0CfYrXLrMxcucG9lyRJkiRJ6gTa9IhQZja0odkXKK10gdLPfS4rjhuK88XAnsBewELgAmBpRNwdEaOQJEmSJEnqotplk9uI2AUYA3ynKOoJRGM1UJeZ8yklW8YBjwNPAscDI4HzWrnv6IiYHRGzGxrakuORJEmSJEna+CpOsETEZsBk4CuZ+UpRvJTSI0EAfYAlAJl5fmbuR+kRoqtLRbkKWNPSvTNzfGbWZ2Z93759K+2qJEmSJElSh9igBEtEXB4RRxanvwBuycz7yppMB0YUx4cX543XDgLmZeZyoGdEBFC3If2QJEmSJEnqDDZ0BUs/YJsiWXIicExEPFT8fRSYCPSKiFnAQOCasmvHAFcVx1OBOcCUDeyHJEmSJElS1fVoa8PMnFh2fGZZVc9WLjm5lfuMKjseC4xtax8kSZIkSZI6o3bZ5FaSJEmSJKmWmWCRJEmSJEmqkAkWSZIkSZKkCplgkSRJkiRJqpAJFkmqQRGxbUQ8EBGXNSuvi4ifRMTDEfFERAwvyodFxKKyX4zbuSifUrQbVpwfFhEXb/QBSVKNM65LUvWZYJGkGhMRPYCpwNzmdZm5CvhtZg4GjgN+XFT1Bq7PzKHF38KIGAi8ChwNnFW0OwcY19FjkCS9x7guSZ2DCRZJqjGZuZrS5HlWK/X3FIeLgG2L417AsmZNexdtXgL6FN+KzsrMle3eaUlSq4zrktQ5mGCRpBqUmQ1taPYFSt+INjojImZGxDURsQWwGNgT2AtYCFwALI2IuyNiVLt3WpLUKuO6JFVfj2p3QJLU+UTELsAY4ACAzJwATIiIAH4CfDUzvx8RDZSWjt8C7AAcDxwC3Avc2sJ9RwOjAXbdddeNMBKp6xtwyV1Ve+0FV4yo2murfRnXJanjuYJFkrSWiNgMmAx8JTNfKa/LzATuAT5anJ+fmfsBw4GriyargDUt3Tszx2dmfWbW9+3btyOHIUkqGNclaeMwwSJJIiIuj4gji9NfALdk5n1l9duXNR8G/LmsbhAwLzOXAz2Lb0PrNkK3JUkJ3lSBAAAgAElEQVStMK5L0sbnI0KSJIB+wDbFpPpEYM+IOKaoGw0cWZy/BbwAnFF27Rjg3OJ4KjAHuHGj9FqS1BrjuiRtZCZYJKlGZebEsuMzy6p6ttD8GeCKVu4zqux4LDC2nbooSfoAjOuSVF0+IiRJkiRJklShNiVYImLbiHggIi5roW6/iHg0Iv4YESOKsh4RcUNEPBIRkyNi86J8SkQ8ERHDivPDIuLidhyPJEmSJEnSRrfeBEtE9KD07OXcVpr8FDgKOAy4KiI2AY4FVmTmPsA84PSIGAi8ChwNnFVcew6ln4GTJEmSJEnqsta7B0tmro6Io4ERwIDyuojoD6zMzEXF+QLg45R+1m1S0exO4OvAE8Ai4CWgT0QMB2Zl5sp2GYkkSZIkSZ3cgEvuqtprL7hiRNVeuxa06RGhzGxopaofsKzsvKEoKy9vLFsM7AnsBSwELgCWRsTdETEKSZIkSZKkLqrSTW57AlF2HkBds/IA6jJzPqVkyzjgceBJ4HhgJHBeSzePiNERMTsiZjc0tJbjkSRJkiRJqq5KEyxLgd5l532AJc3KG8vIzPMzcz9KjxBdXSrKVcCalm6emeMzsz4z6/v27VthVyVJkiRJkjrGBiVYIuLyiDgSeI7Sfio7RUQfSo///AWYTmnPFoDDi/PGawcB8zJzOdAzIhpXvUiSJEmSJHVJ693kthX9gG0yMyPiLOCOovzCzFwVEROBCRExi9KmtqeUXTsGOLc4ngrMAW7cwH5IkiRJkiRVXZsTLJk5sez4zLLj+4G9m7V9Bzi5lfuMKjseC4xte3clSZIkSZI6n0r3YJEkSZIkSap5JlgkSZIkSZIqZIJFkiRJkiSpQiZYJEmSJEmSKmSCRZIkSZIkqUImWCRJkiRJkipkgkWSalBEbBsRD0TEZS3U7RcRj0bEHyNiRFHWIyJuiIhHImJyRGxelE+JiCciYlhxflhEXLxRByNJMq5LUidggkWSakxE9ACmAnNbafJT4CjgMOCqiNgEOBZYkZn7APOA0yNiIPAqcDRwVnHtOcC4Duy+JKkZ47okdQ4mWCSpxmTmakqT51nN6yKiP7AyMxdl5jJgAfBxYDhwV9HsTuBAoDewCHgJ6BMRw4FZmbmywwchSWpiXJekzsEEiyTVoMxsaKWqH7Cs7LyhKCsvbyxbDOwJ7AUsBC4AlkbE3RExqiP6LUlqmXFdkqrPBIskqVxPIMrOA6hrVh5AXWbOpzQpHwc8DjwJHA+MBM5r6eYRMToiZkfE7IaG1v5bQJLUjozrkrSRmGCRJJVbSmmJeKM+wJJm5Y1lZOb5mbkfpaXmV5eKchWwpqWbZ+b4zKzPzPq+fft20BAkSWWM65K0kZhgkSQREZdHxJHAc5Seu98pIvpQWib+F2A6MKJofnhx3njtIGBeZi4HekZE47ejkqQqMa5L0sbXo9odkCR1Cv2AbTIzI+Is4I6i/MLMXBURE4EJETGL0uaHp5RdOwY4tzieCswBbtw43ZYktcK4LkkbWZsSLBFxEXAcsAo4pXg+s7Hu/wNGAwlclZmTi5+Ku45ShvxF4EuZ+VZETAEGABdk5oyIOAz4WGaObc9BSZLWLzMnlh2fWXZ8P7B3s7bvACe3cp9RZcdjAWO6JFWBcV2Sqmu9jwhFxC7ACcAQ4DvAlWV1PYDvFnX7At8vqo4FVmTmPsA84PSIGAi8Sukn5M4q2p1DaRMtSZIkSZKkLqste7AcCPw+M1cD04DBZXVrgNWUNsbqBbxdlA8H7iqO7yzu0RtYRGkJYp+IGA7MysyVlQ5CkiRJkiSpmtqSYOkHLIPSFuLAmoioK87XUHo8aCZwL3B682so/dRbP2AxsCelx4YWAhcASyPi7ohoWoYoSZIkSZLU1bQlwdITiLLzKMoajQauBR7gvc2xyq8JoK7Yt6WB0iNBjwNPAscDI4HzWnrhiBgdEbMjYnZDQ0NbxiNJkiRJkrTRtSXBspTS4z0UP9HWMzNfL87/BdghM7+fmecBe0bER8uvofT40BKAzDw/M/ej9AjR1aWiXEXpUaP3yczxmVmfmfV9+/bd4EFKkiRJkiR1pLYkWB4EDo6ITSntpfJYRFweEUcCrwObRwHYuiibDoworj+8OAcgIgYB8zJzOdCzuK6u3UYkSZIkSZK0ka33Z5oz89mImAQ8Qulnmr8EfB3YJjP/FhG3A3+ktArl5sx8ISImAhMiYhalTW1PKbvlGODc4ngqMAe4sZ3GI0mSJEmStNGtN8ECkJlXAVeVFZ1ZVncZcFmz9u8AJ7dyr1Flx2OBsW3urSRJkiRJUifUlkeEJEmSJEmStA4mWCRJkiRJkipkgkWSJEmSJKlCJlgkSZIkSZIqZIJFkiRJkiSpQiZYJEmSJEmSKmSCRZIkSZIkqUImWCRJkiRJkipkgkWSalBEXBQRj0bEjIjYraz84Ih4qOxveUQMjohhEbGorHznov2UiHgiIoYV54dFxMXVGpck1SrjuiRVnwkWSaoxEbELcAIwBPgOcGVjXWbem5lDM3MosD+wEHgM6A1c31iXmQsjYiDwKnA0cFZxi3OAcRttMJIk47okdRImWCSp9hwI/D4zVwPTgMGttBsBTMvMd4BewLJm9b2BRcBLQJ+IGA7MysyVHdNtSVIrjOuS1AmYYJGk2tOPYlKdmQmsiYi6FtqdBtxQdn5GRMyMiGsiYgtgMbAnsBelb0QvAJZGxN0RMapDRyBJKle1uB4RoyNidkTMbmhoaMchSVLXY4JFkmpPTyDKzqMoe68gYgdg58z8E0BmTsjMjwFDgXeBr2bmfKCB0tLxx4EngeOBkcB5Lb2wE3FJ6hBVi+uZOT4z6zOzvm/fvu07KknqYtqUYGlt06yibruIuCUi/hQR/1WU9YiIGyLikYiYHBGbF+VumiVJ1beU0jJwIiKAnpn5erM2pwC/an5h8c3oPcBHi/PzM3M/YDhwddFkFbCmpRd2Ii5JHaJqcV2S9J71JljWtWlW4b+AP2TmJzPznKLsWGBFZu4DzANOd9MsSeo0HgQOjohNKT23/1hEXB4RR5a1WWsiHhHbl9UNA/5cVjcImJeZy4GexeS+paXpkqSOYVyXpE6gRxvaNG2aFRHTKHtuMyK2AvYBTmx2zXBgUnF8J/B14AncNEtSBxlwyV1Ve+0FV4yo2mtviMx8NiImAY8Aq4AvUYrT2wBExBBgfma+UnbZaRFxDPAW8AJwRlndGODc4ngqMAe4sUMHIUlqYlyXpM6hLQmWtTbNiog1EVFXLBX8Z2AJ8Itihcr1mXl9+TWUnuPsR8ubZk2NiLuBCZl5azuOS5K0Dpl5FXBVWdGZZXUzgSOatb8CuKKVe40qOx4LjG3XzkqS1su4LknV15YES09KG181atw0axWwFfBPlDa+eg14tEiYlG+0FUBdZs6PiMZNs24BdqC0adYhwL3A+xIsETEaGA2w6667ftCxSZIkSZIkbRRt2eR2XZtmLQMez8wlmfkm8DTQv/waoA+lVS5uhihJkiRJkrqltiRY1rVp1t+AnSKid0T0AAYC84HpQOOmBIcX54CbZkmSJEmSpO5nvY8IrWvTrMx8NyIuorSRbQ/g2sxsiIiJwISImEVpU9tTym7pplmSJEmSJKlbacseLOvbNGsGpV8SKm//DnByK/dy0yxJkiRJktSttOURIUmSJEmSJK2DCRZJkiRJkqQKmWCRJEmSJEmqkAkWSZIkSZKkCplgkSRJkiRJqpAJFkmSJEmSpAqZYJEkSZIkSaqQCRZJkiRJkqQKmWCRJEmSJEmqkAkWSZIkSZKkCplgkSRJkrq4iLgoIh6NiBkRsVuzumkRMSsiHoqIfyvKekTEDRHxSERMjojNi/IpEfFERAwrzg+LiIs3/ogkqesxwSJJNciJuCR1HxGxC3ACMAT4DnBlsya9gGGZOTQzv1uUHQusyMx9gHnA6RExEHgVOBo4q2h3DjCug4cgSd1Cj2p3QJK0cZVNxPcB9qc0ET+mrEkv4DOZ+U5ZWdNEPCK+R2kifh+lifhXge8BMyhNxI/r8EFI6vYGXHJX1V57wRUjqvbaG+hA4PeZuToipgE3NKvv0SymAwwHJhXHdwJfB54AFgEvAX0iYjgwKzNXdlzXJan7cAWLJNWepok4MA0Y3Ky+tYl443/t3FncozdOxCWpM+gHLAPIzATWRERdWX1dRDxQ/B3Y/BqgoThfDOwJ7AUsBC4AlkbE3RExaiOMQ5K6tDYlWNa1lLyszW8j4rLi2KXkktR5VW0iHhGjI2J2RMxuaGho94FJUo3qCUTZeRRlAGTmwMzcH/gyMDEitmx2TQB1mTmfUowfBzwOPAkcD4wEzmvphY3rkvSe9T4i1Ial5ETEic3u5VJySeq8egLvlp03TsRXQWkiDlAk1B8snslvcSIeEY0T8VuAHShNxA8B7gVubf7CmTkeGA9QX1+f7T4ySapNS4HdASIigJ6Z+XrzRkXcXgTsXFzTu6jqAywp2pxf3GcKcAYwODNXRcSall7YuC6prWrh0c+2rGBZ51LyiOhFKQFzU1mxS8klqfNqmlSvbyJOKW6vcyKemftRivtXl4pyFdDiRFyS1CEeBA6OiE0pzbsfi4jLI+LIiNg8Ij4EEBF9ge2BF4HpQON/cRxenFO0GwTMy8zlQM/is6J8paMkqQVtSbCsbyn5D4Fvs/Zk2mc6JanzciIuSd1IZj5LacPaR4DLgAspzb+3Kf6mRcTDlL74PC8z3wYmAr0iYhYwELim7JZjgKuK46nAHGBKhw9Ekrq4tvyKUKtLySPis8Abmfl4RPy/za6peCl5RIwGRgPsuuuuH2RckqRWZOazEdE4EV8FfInSr0c0TsTvjoh3gE0pJuIRMRGYUEzEXwJOKbvlGODc4rhxIn7jxhiLJKkkM6/ivaQIwJllx3u30P4d4ORW7jWq7HgsMLaduilJ3VpbEizreqbzi8AXIuJYYAtg04jYBJ/plKROzYm4JEmS1L7a8ohQq0vJM/PszNw+M3egtBTxR5n5bVxKLkmSJEmSash6EyzreaazNRPxmU5JkiRJklQj2vKI0PqWkje2mVh27FJySZIkSZJUM9ryiJAkSZIkSZLWwQSLJEmSJElShUywSJIkSZIkVcgEiyRJkiRJUoVMsEiSJEmSJFXIBIskSZIkSVKFTLBIkiRJkiRVyASLJEmSJElShUywSJIkSZIkVcgEiyRJkiRJUoVMsEiSJEmSJFXIBIskSZIkSVKFTLBIUg2KiIsi4tGImBERu5WV10XETyLi4Yh4IiKGF+XDImJRRDxU/O1clE8p2g0rzg+LiIurMypJql3GdUmqPhMsklRjImIX4ARgCPAd4MrGusxcBfw2MwcDxwE/Lqp6A9dn5tDib2FEDAReBY4GziranQOM2zgjkSSBcV2SOos2JVg2ICPeIyJuiIhHImJyRGxelJsRl6TqOxD4fWauBqYBg8srM/Oe4nARsG1x3AtY1uw+vYs2LwF9is+AWZm5sqM6LklqkXFdkjqB9SZYNjAjfiywIjP3AeYBp5sRl6ROox/FpDozE1gTEXUttPsCMLXs/IyImBkR10TEFsBiYE9gL2AhcAGwNCLujohRHToCSVI547okdQJtWcGyIRnx4cBdxfGdxT3MiEtS59ATiLLzKMreKygl18dQSqyTmRMy82PAUOBd4KuZOR9ooJQofxx4EjgeGAmc19ILR8ToiJgdEbMbGhradVCSVMOM65LUCbQlwbIhGfGmaygF6X6YEZekzmIppaQ3ERFAz8x8vbEyIjYDJgNfycxXyi8sPgfuAT5anJ+fmftRSqxfXTRZBaxp6YUzc3xm1mdmfd++fdt/ZJJUm4zrktQJtCXB8oEz4s2uCaDOjLgkdRoPAgdHxKaUVhg+FhGXR8SRRf0vgFsy877GCyJi+7LrhwF/LqsbBMzLzOVAz2Jy31IiXpLUMYzrktQJ9GhDm6XA7vCBMuJNWXSgD7AEShnx4popwBnA4MxcFRGtZsSB8QD19fX5wYYmSWpJZj4bEZOAR4BVwJeArwPbFJPqE4E9I+KY4pLRwJHF+VvAC5RieKMxwLnF8VRgDnBjhw9EkgQY1yWps2hLguVB4KyI+DfgsxQZcWB2Zv6GFjLiwHRgBHAvcHhxDqydEY8IM+KSVAWZeRVwVVnRmWXHPXm/Z4ArWrnXqLLjscDY9uijJKntjOuSVH3rTbBsYEZ8IjAhImZR2tT2lLJbmhGXJEmSJEndSltWsGxIRhzg5FbuZUZckiRJkiR1K23Z5FaSJEmSJEnrYIJFkiRJkiSpQiZYJEmSJEmSKmSCRZIkSZIkqUImWCRJkiRJkipkgkWSJEmSJKlCJlgkSZIkSZIqZIJFkiRJkiSpQiZYJEmSJEmSKmSCRZIkSZIkqUImWCRJkiRJkipkgkWSJEmSJKlCJlgkSZIkSZIqZIJFkiRJkiSpQm1KsETERRHxaETMiIjdmtXtV9T9MSJGFGU9IuKGiHgkIiZHxOZF+ZSIeCIihhXnh0XExe09KEnSuhnXJal7Ma5LUvWtN8ESEbsAJwBDgO8AVzZr8lPgKOAw4KqI2AQ4FliRmfsA84DTI2Ig8CpwNHBWce05wLh2GIckqY2M65LUvRjXJalzaMsKlgOB32fmamAaMLixIiL6Ayszc1FmLgMWAB8HhgN3Fc3uLO7RG1gEvAT0iYjhwKzMXNlOY5EktY1xXZK6F+O6JHUCbUmw9AOWAWRmAmsioq55XaGhKCsvbyxbDOwJ7AUsBC4AlkbE3RExqsJxSJLazrguSd2LcV2SOoEebWjTE3i37DyKslXF/41mdXXNygOoy8z5EdFAaYnhLcAOwPHAIcC9wK3NXzgiRgOji9OVEfE/bRtWu+vD2h9MbRY/bOeebFwbPG6o3bHX6rihS4+92uPuX/EdPhjjevX/zaulVscNxvUNUqtjN64b17sY49sG6MJjr9VxQxeI621JsCwFdgeIiAB6ZubrZXW9y9r2AZY0K28sIzPPL+4zBTgDGJyZqyJiTUsvnJnjgfFtGUhHiojZmVlf7X5sbLU6bqjdsTvummFcr71/c6B2xw21O/ZaHTfU3NiN67X1772WWh274649XWHsbXlE6EHg4IjYlNKzmY9FxOURcSTwHKXnM3eKiD6UlhP+BZgOjCiuP7w4ByAiBgHzMnM50LP4EKhDkrSxGNclqXsxrktSJ7DeFSyZ+WxETAIeobTM8EvA14FtMjMj4izgjqL5hUWGeyIwISJmUdok65SyW44Bzi2OpwJzgBvbYzCSpPUzrktS92Jcl6TOIUr7YGldImJ0sfyxptTquKF2x+64VStq9d+8VscNtTv2Wh031PbYa1Et/3vX6tgdd+3pCmM3wSJJkiRJklShtuzBIkmSJEmSpHUwwSIJgIg4uNp9kCS1H+O6JHUvxvXOzwSLiIhdIuInETExIr7QrO731epXR4uI3SLiFxHxnxHRLyIujIi/RMQdEbF7tfvXkSJi32Z/+wE3NZ5Xu38dJSIOKzseEBH3RsRLEXFXROxZzb5J7alW4zrUbmyv1bgOxnbVjlqN7cZ143pXiuvuwVImIr69rvrMvHxj9WVjiojpwK+ARcAXgJ2BkzLzlYiYkZnDqtrBDlKM+xfAvwCDgZuA2yn9vOGpmTm8it3rUBGxCJgLLACiKD4WmAxkZp5Wpa51qIh4MDP3LY5vo/T/93cD+wIXZ+ZB1eyf2p9xvbbiOtRubK/VuA7G9lpkbK+t2G5cN67TheL6en+mucZ8Fvgr8Gi1O7KRbVq2G/OdRcZwWkScBnTnDNwmmXlT8bOGczNzXFF+Y/Fzht3ZR4HvA68Dl2XmGxHxufz/2bvzcK/KcuHj3zsGBxwZxOkojrxHy2Mn7KBCGpIpqCmhpqjHoRfNKSm0znF4ieocUum1skxywE6KWoaJipKoiCQmoub4qokjg4BDzojc7x9r7e2P7d6w5cdmT9/Pde3rWut5nrXWszaX9/55/54h87hm7tea1C0z/1geT4mIc5q1N2oqxvX2Fdeh/cZ243rB2N4+GNvbV2w3rhvXW01cN8GyvEOAm4BzM3Nxc3dmDXo1Ir6YmX8FyMxbI+Ip4FqgV7P2rGkti4gNM/PNiPi/derWb5YerSGZ+QZwSkT0ByZGxCUru6aN2CUipgOLga1rCiPiM8B6zdYrNSXjOu0qrkM7je3tOK6Dsb09MrbTrmK7cd24DrSOuO4UoToiokNmftTc/ViTImIL4J3yP+LK8i7AqZn5k+bpWdOKiH4UWfBFdcq3Bo7MzP9unp6tWRHRGfgPYGhmfq65+9PUImJDoCvQKTOfLsu6Artm5p3N2jk1CeP6cuVtOq6DsR3aX1wHY3t7ZGxfrrxNx3bjunG9NcV1EyySJEmSJElVchchSZIkSZKkKplgkSRJkiRJqpIJFrU4EXFuRDwWESMb2X6PiNioqftVjTp7uf8qIjpGxN4RcWNz9kuS1gTjuiS1LcZ1qX4mWNQSHQ0MyMwLG9l+BNBiA3ZE7AwcVnOemSdn5tJm7JIkrWnGdUlqW4zrUj1MsKhFiYhzga2AP0XEaRExPSL+FhHfLOu7RMSEiPhLREyOiCHAV4DfR8TxEbFuRFwdETMiYlJEbFJeNz4izoyIeyNi93qe26u85s6I+FlEjK+4bu/y+OCK8q+V93ooIv5PWbZ3RPwhIm6KiEcj4qSI6ABcDOwfEfeW7Z6vm8GPiO0iYkpE3FdzP0lqC4zrxnVJbYtx3biuhplgUYuSmT8E5gP7A5dkZn/gy8DZZZNTgaczcw9gUGb+EXgYODQzryjrn8nMPYHxwJiK2382M/tl5n31PHoUcHFmDgCWNKKrt2RmP2A3iv3pO5blXwKOBPYAvlduH/gDYHLZviEXASdm5u7AwIjo3Yg+SFKLZ1w3rktqW4zrxnU1zASLWrJDyyzyH4GNy7LdgSkAWf8e43sAfy6PbwP2rqibvIJn/SswrTy+uxF92zsi7gbuBDYA1ivLH8rMtzPzLSAacZ8auwNXlvfcGNjyU1wrSa2FcV2S2hbjulSh48qbSM1iHeBnwM7A68CisvzTBMFg+STi+ytpW/MHoHK+ZeUfhXUrjq8ABmbm0xHxckX5e5+if3UNyMxlVVwvSS2ZcV2S2hbjulSHI1jUUn0AvJOZC4HKoXqzgH0ByvmSAO/ycUb6LzX1wH7AzEY+72Fgr/K4f0X5QmDb8njvivJ1gOcjYjtgs5Xcu7J/DZkFDAaIiA0qhjBKUlthXJektsW4LtVhgkUt1TLgzoi4jyKQPV2W/wz4XET8hXLoIXANcG1EHE+xQNUOETEDOAn4XiOfNwoYERF3AD0ryi8HTo+IO4F/VJT/kuKPwfeB6Su59yPAFhFxV0R0aqDNaeXz/wLcTvEHQZLaEuO6JLUtxnWpjqh/WpzUfpWrkB+bmcc2c1ckSauBcV2S2hbjuloqhzWp3Skz58dXFN1eroYuSWqFjOuS1LYY19VamWBRu1NuD3dFc/dDkrR6GNclqW0xrqu1coqQJEmSJElSlVzkVpIkSZIkqUomWCRJkiRJkqpkgkWSJEmSJKlKJlgkSZIkSZKqZIJFkiRJkiSpSiZYJEmSJEmSqmSCRZIkSZIkqUomWCRJkiRJkqpkgkWSJEmSJKlKJlgkSZIkSZKqZIJFkiRJkiSpSiZYJEmSJEmSqmSCRZIkSZIkqUomWCRJkiRJkqpkgkWSJEmSJKlKJlgkSZIkSZKqZIJFkiRJkiSpSiZYJEmSJEmSqmSCRZIkSZIkqUomWCRJkiRJkqpkgkWSJEmSJKlKJlgkSZIkSZKqZIJFkiRJkiSpSiZYJEmSJEmSqmSCRZIkSZIkqUomWCRJkiRJkqpkgkWSJEmSJKlKJlgkSZIkSZKqZIJFkiRJkiSpSiZYJEmSJEmSqmSCRZIkSZIkqUomWCRJkiRJkqpkgkWSJEmSJKlKJlgkSZIkSZKqZIJFkiRJkiSpSiZYJEmSJEmSqmSCRZIkSZIkqUomWCRJkiRJkqpkgkWSJEmSJKlKJlgkSZIkSZKqZIJFkiRJkiSpSiZYJEmSJEmSqmSCRZIkSZIkqUomWCRJkiRJkqpkgkWSJEmSJKlKJlgkSZIkSZKqZIJFkiRJkiSpSiZYJEmSJEmSqmSCRZIkSZIkqUomWCRJkiRJkqpkgkWSJEmSJKlKJlgkSZIkSZKqZIJFkiRJkiSpSiZYJEmSJEmSqmSCRWrBIuLYiBjf3P2QpLYqIkZFxKjm7ockSWr9TLBIqyAiOkfE15q7H5KklicivhIRG5XH60fERRHxXETMi4j/GxFR1kVE/DwiFkfEyxFxTPP2XJJajog4LiIej4jXImJ+RJwfEeMj4u3yfE5EnFO2nRwR36lz/bCImN48vVd7ZYJFWjUDgEOauxOSpBZpNLBRebw+8BrwWWAn4GvlD8DRwJeAbYD9gZ9HRK812VFJaoki4mTgh8CJQDegNzC+rL4wMzel+Dz+rYg4EJgIHFTnNl8D/rhGOiyVTLCoRYiIdyPihIj4f+W3fPuV5U9FxFcq2v0wIn6zgvt8t7z+1Yj4r7KsR0T8sfzm8OGI6FfR/vmI2D8ini2/YewVEQ9FxLciYm5EHFrPMz4PXAEcXmbP+5dDzP8jIm4uv4XsEBGbRMQtZZspEbFpef2xEfHbiLi+7NNdEdG1rPtM+e3mvIh4APjX1fQrlqQm0Zrid3ndOhHxP+U9p1EkN2rqOpb3ejkiHouIvmV5vfeOiP8s+/FsRBxUlo0Dvgg8EBF/ysy5mTk6M9/NzNeBvwI7lo88BBiXmf/IzEeBPwMHfup/BElqQyKiAzAKOC0z783Cm5n5RGW7zJwD/IUipv4J2D0iNi7v0RnYjyLxIq0xJljUUqxD8e3e/wKOA66OiPUoguKginY1GepPiIjBFFnu3YHNgJ+XVb8C/g5sDpwA3FATfEvfBXbNzIxDBx0AACAASURBVDPK838GdgC2zMzf131OZj4E/CdwXWZumpk1Qw+/B/w4M7fMzI+AXwJ/KTPsDwAXVNzm6LJ+c2A+MLwsP5wiG78jsG95LEktWauJ36UzgE2ArYCjgK9W1J1I8S1pL2AEMCEiOtZ377LPhwE7U3xremVEbJyZw4GXgN0yc7mppBERwK7A7LJoB2BORZM5ZZkktWf/C+gKTFpRo4jYBegPzMjMBRQJ7MFl9QDg75n5fBP2U/oEEyxqSX5bZqinAYsovgG8kfIDekRsBWwLTG3g+qHA/2Tmgsz8KDPnlxnwg4GLyns/CDzKx8EX4LLMfLvifC3g/Mxc9in7PzMz7yv7WvPccWXdtcBXKto+lZnTMjPL99m+LB8EXJuZb5XfdF79KfsgSc2hNcXvQcD4zPwwM1+i+NazxteBKzJzaWb+GdiAj+Nz3Xt/Hbg6M98pv1V9Hvi3FTwX4FSKpHrN72Fd4P2K+veBLiu5hyS1dRsDCzNzaQP1IyNiPnAl8J3MnFmWV04TOginB6kZmGBRS/KPiuNFFN8w/hVYLyK2Aw4AJmfmBw1cvxnFB9dKPYCOwKsVZa8CW1Sc172GzPxEWSNUXtO9fO6j5R+AO1j+Q3Nlf5aWbWv6u6iBdpLUUrWm+L2iOLsZcGk5tXM+0Ikintd3782Acyrabk/xjWu9yulN3weOKZPrAO8Ca1c0Wxt4ZyX9l6S27k2gaznqrz4XlqPIv5CZ11SUTwS+Wk4PanDUpNSUTLCoJelWcbwJ8Gr5IfRPFKM/9qP4RrQhrwKb1ilbSJHA2KyibFNgXpV9zZXULwY+Av65/APQMzPXb8T1i1j+99Dgh3VJakFaU/xeUZxdAJxQxu1NM3ODzLy3gfssAEZVtN2w4oP+cjE+InagGMn4jcx8saLqGSrWgKEY5fPMKryTJLUl/w/4gGIR8EYr12R5Dvgm8F5mPtYEfZNWyASLWpLjozCA4gPvX8vyicA+QF/glhVcfxNwdET0AIiIrcu1UG4EvlMuIPtFioVjp1TZ19co5u9TX3a9HNJ4E/Dt8p06RsROjbjvFOCIiNggii0+h1XZT0laE1pT/J4CHBcRnSNiC4ppSDX+CJwYEeuU/dhlBff5I3BMxSLlO0ZEzWiU14Cty99JD4p3H1GxZleNicDwMuZ/DhjIStYckKS2LjOXABcBv4qIz0KxaG1EbN6IyycCZ+LoFTUTEyxqSV6k+ObucuDoinn1d1NksGdn5j8auBbgBuB3wIMRsRA4pSw/GdgamEsxV/MbqzgFqNJUYK2IeBH4cgNtTgI+B7wCvECxgO3KXA1Mp/g93EXxTpLU0rWm+D2WIgHyEnA9UDm8/FfA34Cnymk/5zd0k8y8iSJmz4qIBcBVQOey+v8C11F8wD+JYmTKL2qmE0WxSxzA/wD3UCxuextwugsyShIA/4cixt4cEa9RrHP19UZcN5FioXITLGoW8fE0YKn5REQCvTLzhebuiySp8YzfkiRJBUewqCVpaCGr5RtF7FHxLWDNzzUrv3IVOhRxeD3P+klTPEuSWjHjtyRJavccwaIWofwGdBuHRktS62L8liRJKphgkSRJkiRJqpJThCRJkiRJkqpkgkWSJEmSJKlKHZu7A43VvXv37NWrV3N3Q5JWuwcffHBRZvZo7n6sacZ1SW2VcV2S2pbGxvVWk2Dp1asXs2bNau5uSNJqFxHtcntb47qktsq4LkltS2PjulOEJEmSJEmSqmSCRZIkSZIkqUqtZoqQpOX16tWLF15olyOQW7ytt96a559/vrm7IakVMrY3P2O4pNXJuN781mRcN8EitVIvvPACmdnc3VA9IqK5u7BSEbERcCNwd2aOqijfFzivouk/AwcCHYDrgOfK8sMz85WImAj0Ak7PzOkRMQjYOTMvaPq3kNoeY3vzaw0xXFLrYVxvfmsyrjtFSJLamYjoCEwCnqpbl5lTMrNfZvYD9gZeAR4AugFX1tSVyZXewOvAEOCk8hYnA5esgdeQJEmSWhQTLJLUzmTmUoqkyMyVNB0MTM3MD4GuwKI69d2AucBLQPeIGAjMzMy3V3OXJUmSpBbPBIsktUOZubARzY4Hrqo4/2ZEzIiIX0bEOsA8YHtgR4qRLqcDCyLi1ogYuto7LUmSJLVgrsGiNqnX929ptmc/P2Zwsz270ocffsjrr7/OJptsAsCrr75Khw4d6NatGwCLFi1i3XXXZd11111tz3zmmWfYbrvt+MxnzN22dhGxKbBFZj4MkJlXAFdEMYn1Z8B3MvPHEbGQYkrQ9cCmwBHAfsAU4A/13Hc4MBxgq622WuX+Ned/49By/jtX+2Jcl9omP7e2X8b1tsffahvX6/u3NNuPmteCBQs4+eSTa8/POOMMnnrq4yU3Jk2axPDhwwE49thj6du3L//6r//Knnvuyaabblq70vasWbMYNWoUAPfccw/vvfcehxxyCG+++eZyz1u8eDFHHnkkH3zwAT179mTvvfeu/fnyl7/8if6df/75vPvuuyxZsqT2/pXef/99zjrrLDKTL37xi7z77rsrfN8ZM2aw11570bdvXw4//HCWLl26XP1+++1X73N+85vf0LdvXz7/+c9z/vnnA/Dyyy9zyCGHsOeee9K/f39efPFFAObNm8eAAQP4t3/7N374wx+usD9twDHA1XULs1ilbTKwU3l+WmbuBQwELiqbLAGW1XfTzByXmX0ys0+PHj2arPNSW2RcX/qJNn/729/o378/u+22G5dddhnQcKyur60kNSfj+vJxPTMZPnw4e+65J/369ePRRx+tLT/77LP53Oc+x+67715btuGGG9KvXz/69evHzTffvMJnrymOYJHaoAkTJjB27FgA+vTpA8Cjjz7K008/zfnnn8+AAQM47rjjyEyWLSv+P/gXv/gFZ511FmeddRY33HADAEuWLGHp0qU88cQTAJx33nnccccdvPfee8uthv7ee+/x9a9/nbPPPpt11lmHDTfckL333ru2/p577lmuf1OmTOHxxx+vzcY//vjjjBs3rvYPCMDaa6/NJptswt133837779Pp06dVvjO6623HhMmTGDzzTfniCOO4KabbmLIkCEAXH311fV+MAfYbrvtmDZtGp/5zGfYcccdOe644+jSpQvf+9736Nu3L5deeikXXnghP//5zznvvPM47bTTOPjgg9lrr70YMmQIO++884r/MVqJiBgNzMrMm8qiY4ABFfWbZOar5Wl/4G8VdX2BZzJzcUR0Kke5dF5DXZfaBeP68nG95l0OO+wwJkyYwOc///na8vpi9Q477FBvW7UsjuRQe2Jc/2RcnzFjBi+//DIzZszgvvvuY/To0fz+979n3LhxzJkzh0ceeaR25M2bb77JZz/7We69997G/9LXABMsUhu0YMECRo4cyTe+8Q3GjBnDlltuyVFHHcWFF17Ia6+9xu23386kSZPo27dvbZB65ZVXeOONN3j88cdr73P77bdz44038thjjzFmzBieeuop+vXrx1NPPcVXvvIVOnTowNixY8lMDjnkELp06cK0adPo2rUrBxxwQO19KgPfU089xciRI5k2bVpt2bhx49hjjz3YYostGDy4+IDzve99j6lTp3Lttdfy9NNP12arAbp3785tt93Gc889x6BBg3jqqaf4l3/5l9r6zTffnDfeeAOA1157jWuuuYYjjzyydiRKpQEDanMIdO3albfeeottt92Wvn371t5rxowZAEydOpWLL76YiGDQoEFMnTq1zSRYgJ7A+gARsScwpyKhAnB8RBwKvA+8AHyzom4kcEp5PAmYDfyuyXsstSPG9Y/jeo1p06ax6667fiJhUl+snjt3br1tJam5GNc/Gdc32GAD5s+fz9KlS5k3bx4bbLABAL/97W+5/PLLl5vW9Nprr9G9e/eq/g2aggkWqY0699xzueiii5g7dy6dO3fm4osvZt68eYwdO5a+ffvSpUsXLrvsMo466iig+KD68ssvM3HiRDbeeGMA5syZw2abbcZhhx3GO++8w3/9139x/PHHs99++3Httdey0UYb1T5v8803Z/Dgwdx555107dqV73//+7V1NcH0iSee4NBDD2XChAm1zwDYeOON+dOf/sQ+++zD5Zdfzr777stPfvIToJib2rdvX2bNmlXbfo899gCKrPkuu+yy3Ht/+OGHTJkyhREjRgBF4B89enTtEMOGPPvssyxdupRtt912ufIbbriBAw88EIB3332XtdZaC4AePXrw3HPPrfCeLV1mjq84PrHieAZwYJ22Y4AxDdxnaMXxBcAFq7uvkozrNXG9xuOPP85aa63F1772Nd566y3GjBlTO0S9bqxetmxZvW0lqTkZ15eP67vssgv77bcfu+22G507d+amm4qB1U8++SQTJ05kypQp7LrrrowdO5YPP/yQhx9+mC996Ut069aNn/70p2yzzTbV/YOsBiZYpDbqiCOOYMCAAVxzzTX06NGDr3zlK1x33XUAbLjhhmy55Za1bd99912OPfZYevfuzVprrVU7YqNbt2707NmTJ598kv3226/Bb/4efvhhDj74YI466iieeOIJvvSlL9XWPfnkk6y11lr8/e9/Z7PNNuOqq67inHPO4e9//zuLFi2qDYTz58/nnnvuYb311lvu3n/729/Ycccd+e53v8t///d/07lzZ4oZKMUfieuvv3659ueeey5Dhw5lyy235K677mLdddflC1/4wgoTLEuXLuWEE07goosuWq781ltv5eWXX2bo0CJ/sGTJktq6zFzuXJKamnF9y+XK33nnHRYsWMBNN93Eiy++yGGHHcbs2bPrjdUNtZWk5mRcXz6uL1q0iMmTJzNixAiuvvpq7rjjDoYNG8bbb7/NHnvswX/8x39w7LHHcuONNzJkyBBeeOEFoPhCdPjw4fz5z3/+1P8Gq5sJFqkN+vKXv8z06dN57LHHWLBgAR988AGPPfYYO++8c71B9+2332b69On07NmTK6+8kh133BGAYcOGMWvWLJ588kn23HNPBg8ezOLFi5cbcnjNNdewxRZb8POf/5zZs2fz61//mnnz5tXe+7nnnmOTTTZh++235/jjj6dPnz7cdNNNXH755cyfP5+zzz4bKNZCqS/r/Jvf/IYhQ4Zw55138pvf/IZTTjmldh5qXRMnTmTWrFncfvvtAFx//fXccMMNXHfddbz33nt89NFHLFu2jNGjRy933ciRIz+xuNdzzz3HmWeeyR133FH7B2K99dbj/fffZ+2112bRokVsuummn+afRZJWmXH99k/Ude/enX333ZfOnTuz/fbb1w41ry9Wr7feevW2laTmYlz/ZFy/+uqr+epXv8oxxxzDYYcdxmc/+1mGDRvGNttsw1577QXA7rvvzrPPPrvcdYMGDeL0009v5G++aZlgkdqYyZMn8+Mf/7j2/OWXX67NSANce+21XHTRRXTv3p033niDb33rW7z//vtEBL/+9a9ZvHhxbcCu65ZbisXn6hty2LVrVwB+//vfc/nll3PCCScAcOqpp3LsscfWLt4FxTeKl156KRdffDFQfAu59tprf+J5s2bNYsaMGVx88cV84QtfqJ2SU7Ng1wsvvMC3v/3t2nmnP/jBD5g6dSodOnQA4JJLLuGSSy4BYPz48Tz//POMGjWKm266iVmzZjF69GjGjx/Piy++WLtQGBR/wA4//HCuuOIKNttss9ry/v37M3nyZA4++GBuvfVWfvrTn678H0SSqmRc/ziuAxx88MH87Gc/Y8CAAZx88smcccYZzJ07t3Zb0/pi9YYbblhv27YkIjYCbgTuzsxRdeo2Bi4FdgT+kpknR0RH4PKy7EXg3zPz/YiYCPQCTs/M6RExCNi5nAIqaTUwrtcf17t06VK7E1HldM8vfvGL3H333ey999489NBD7L///ixevJiNNtqIDh06MH369E9MQ2oujUqwrChgV7S5DZiZmaMM2FLz2X///dl///1rzysXzar00ksvMWnSJK677jqeeOIJzjnnHM455xwATjjhhNpRG6ti9uzZbLDBBhx66KEAy93rH//4ByeeeCK77LJL7fz3uXPnUnfL3vvvv5+jjjqKP/zhD3Ts2JFtt92WbbfdlhdeeKE26bF06VLmzJkDFKNQ3nrrLb72ta8B0LdvXy688MJ6+/fWW2+xYMECAE466SR22mkn+vfvD8C3vvUtXnrpJebMmcN3v/tdANZaay2mTp3K+eefz1FHHcWYMWPYf//9l/sjJElNxbi+fFyfM2cOS5cuZYcdduCggw6qnedfM82zoVhdX9u2ovzsPQl4vIEmvwLuyszDKsoOB97IzN0j4kfACRFxB/A68B3gR8B04GTgG03WeakdMq7XH9eHDRvG5MmT2XPPPVm2bBm/+MUvAPjJT37Ccccdx9lnn03v3r058MADueuuuxg5ciRdunRhrbXWqv1StbmtNMHSiIBNRAyrcy8DttTC/dM//RP33XcfW2+9Nffff39t+RFHHMHs2bM/sSr3zTffzKhRo2rPBw4cCMCxxx7LqaeeulzbCy64gE6dOjFixAimTJnCf/7nfwLF9nB77703RxxxBCNHjgTgjDPOYNKkSZx55pm11y9ZsoTTTz+dCRMm1C649eabbzJgwADee++92sTJdtttxyOPPALAbbfdtsL3PfbYY2uPhw0bxrBhwwB4//33621fuehXjS222IK77rprhc+RpObSXuJ6TT3AaaedxmmnnbZcfUOxur62bUVmLo2IIcBgii8za0VEF2B3YFidywYCE8rjm4GzgIeAucBLQPeIGEjxBerbTdd7SQ1pj3G9clR5jc033/wTU4r22WcfHnrooXrv15yicm/sBhtF9KAM2PUMOewK/A9wA7BVOYLlSmBCZk6JiL4UAftCYBAwCriFYpeJvpn5o8Z0tE+fPlm5KrEap9f3b2m2Zz8/ZnCzPbs9vHdE0Jj/fluaZcuWLbfFWkMys6qsfHP6tP82EfFgZra74TDVxPXm/G8cmje+qW1rjbG9rcX11fFv0FxxPSKOpc7n9YjYFfg18CjQG7gyM6+MiFuBczJzdkRsB/wWOAr4b2A0MBLoTvFF6yHAFZn5hxU9v9rP6+3h81t92ut7txfG9ea3JuP6yn9rQGYuXEH1T4DzgMpVbHoCi8rjheX5PGB7imlDrwCnAwsi4taIGIqkdqExwRpoFcFakmRcbwW6AP8EnAt8FRgRET2BTkDNP0oAnTNzDsVn90uAB4FHgCOAg4FTqUdEDI+IWRExa+HCFf0vg6TWwri+6hr3m2tARHwZeDczH6xTZcCWJEmSmt8i4MHMnJ+Z71FM+98aWADUrPbbHZgPkJmnZeZeFFOILiqKcgnLf5laKzPHZWafzOxTd30GSWpvqt1F6DDg6xFxOLAO0CEiPsMKAjZAudjtN4E9MnNJRDQYsIFxUAw5rLKvkiRJUrsQEaOBWRRT8zePiG7AmxTThOYA0yiWAJgCHFCe11zbF3gmMxdHRKcovqbuvIZfQZJanVUawRIRoyPioMz8VmZukpmbAt8GLszM8/g4YMMKAjZgwJYkSZJWv57A+pn5ETCCYiHb+4DLyun/44GuETGTIunyy4prRwJjy+NJwGxg4hrqtyS1Wqs6gqUnsP4K6scDV5QB+yXgmIq6kcAp5XFNwP7dKvZDkiRJEpCZ4yuOT6w4nk6xk1Bl2w+Boxu4z9CK4wsoNqeQJK1EoxMsDQXsBuoN2FIT23rrrV1YqoXaeuutm7sLasPcbaJtM7Y3P2O4pNXJuN781mRcr3YNllbBD6Nqi55//vlPlLl1rSS1bvXFdklS62Vcb1+q2kVIkiRJkiRJJlgkSZIkSZKq1i6mCEmSpNbN6b6SJKmlcwSLJEmSJElSlUywSJIkSZIkVckEiyS1QxGxUUTcHRGj6qmbGhEzI+LeiDi3LOsYEVdFxH0RcV1ErF2WT4yIhyKif3k+KCLOXKMvI0mSJLUAJlgkqZ2JiI7AJOCpBpp0BfpnZr/M/GFZdjjwRmbuDjwDnBARvYHXgSHASWW7k4FLmqzzkiRJUgtlgkWS2pnMXEqRFJnZQJOOmflhnbKBQM0qozcD+wDdgLnAS0D3iBgIzMzMt1d/ryVJkqSWzV2EJKkdysyFEdFQdeeIuLs8/mFmTgV6AovKsoXl+Txge2BH4BXgdGBSRNwKXJGZf2ii7kuSpFauOXeHA3eIU9MwwSJJWk5m9gaIiG2Ae8qpQJ2AmoxMAJ0zc05ELKSYEnQ9sClwBLAfMAX4RIIlIoYDwwG22mqrJn4TSZIkac1xipAkqV6ZOYdiCtAWwAKKKUEA3YH5ZZvTMnMviilEFxVFuQRY1sA9x2Vmn8zs06NHj6Z+BUmSJGmNMcEiSSIiRkfEQRGxdkRsUJb1ADYBXgSmATVjaQ8oz2uu7Qs8k5mLgU5RzD3qvEZfQJLauRXtDlfR5raaeneHk6TVzwSLJAmKNVXWL3+mRsRfKBazPTUzPwDGA10jYibQG/hlxbUjgbHl8SRgNjBxDfVbktq9RuwOR0QMY/nlAdwdTpJWM9dgkaR2KjPHVxyfWFG1Wz1tPwSObuA+QyuOLwAuWH29lCStTGYujYghFCMNe9Wtj4iuwJHANUDNAlgDgQnl8c3AWcBDuDucJK0yR7BIkiRJrVxmLlxB9U+A81h+fazG7g63ICJujYihSJJWqFEJlobmdEZE54j4WUT8pZyrObAsd06nJEmS1Mwi4svAu5n5YJ2qeneHo0i2XAI8CDxCsTvcwcCpDdx/eETMiohZCxeuKMcjSW3fShMsK5rTWe4UcVtm7gF8A/hpWeWcTkmSJKn5HQYcERHzgZ8BIyNiNO4OJ0mr3UoTLJm5lCIpMrOB+snl4Vxgo/J4IHBLeXwzsA9FAHdOpyRJktTEanaHy8xvZeYmmbkp8G3gwsw8D3eHk6TVrlFThFYyp7PG1ylGuoBzOiVJkqTmVLM7XEPG4+5wkrRarZZdhCJiS4pAPKAsqndOZ0TUzOm8HtiUYk7nfsAU4A/13Hc4MBxgq622qlstSZIkqbSC3eHqq3d3OElazareRSgi1gKuA87IzFfLYud0SpIkSZKkdmOVEiw1czrL00uB6zPzjoomzumUJEmSJEntxqqOYOkJrF8mS4YBh0bEveXPTjinU5IkSZIktSONXoNlBXM6OzVwiXM6JUmSJEmq0Ov7t6y8URN5fszglTfSKqt6DRZJkiRJkqT2zgSLJEmSJElSlUywSJIkSZIkVckEiyRJkiRJUpVMsEiSJEmSJFXJBIskSZIkSVKVTLBIkiRJkiRVyQSLJLVDEbFRRNwdEaPqlHeOiJ9FxF8i4qGIGFiW94+IuRFxb/mzRVk+sWzXvzwfFBFnrvEXkiRJkpqZCRZJamcioiMwCXiqbl1mLgFuy8w9gG8APy2rugFXZma/8ueViOgNvA4MAU4q250MXNLU7yBJkiS1NCZYJKmdycylFEmRmQ3UTy4P5wIblcddgUV1mnYr27wEdC9Hu8zMzLdXe6clSSu0CiMTO0bEVRFxX0RcFxFrl+WOTJSkVWSCRZLaocxc2IhmX6cY6VLjmxExIyJ+GRHrAPOA7YEdgVeA04EFEXFrRAxd7Z2WJNVrFUcmHg68kZm7A88AJzgyUZKqY4JFkvQJEbElMBL4AUBmXpGZOwP9gI+A72TmHGAhxQfvB4FHgCOAg4FTG7jv8IiYFRGzFi5sTI5HkrQyqzgycSBwS3l8M7APjkyUpKqYYJEkLSci1gKuA87IzFcr6zIzgcnATuX5aZm5F8UH9YvKJkuAZfXdOzPHZWafzOzTo0ePpnwNSWpXVmFkYk8+nvq5sDx3ZKIkVcEEiySJiBgdEQeVp5cC12fmHRX1m1Q07w/8raKuL/BMZi4GOkVEAJ3XQLclSY1Ud2Qi0AmImmqgsyMTJak6JlgkSVB8c7l+mSwZBhxasSXzTsDxEfFgRMwAegG/qLh2JDC2PJ4EzAYmrrmuS5JWpIGRiQsopgQBdAfmgyMTJakaHZu7A5Kk5pGZ4yuOT6yo6lRP8yeAMQ3cZ2jF8QXABaupi5KkVRQRo4FZmXkT9YxMBKYBg4EpwAHlec21tSMTI8KRiZLUSI0awdLQtm9l3V4RcX9E/DUiBpdlbvsmSZIkNZ+VjUwcD3SNiJlAb+CXFdc6MlGSVsFKR7BUbPv2eANNfgHsBywB7o2IyVRs+xYRP6LY9u0Oim3fvgP8CJhOse3bN6p+C0mSJKmd+5QjEwGObuA+jkyUpFWw0gRLZi6NiCEUQwh7VdZFxNbA25k5tzx/HvgsxZzNCWWzm4GzgIdw2zdJkqRPpdf3b1l5oyby/JjBzfZsSZJam0ZNEVrBtm+V27vBx1u8ue2bJEmSJElqN6rdRahyezfK48647ZskSZIkSWpHqk2wVG7vBh9v8ea2b5IkSZIkqd1YpQRLRIyOiIOAv1Osp7J5RHSnmP7zKB9v+wYr2PYNcNs3SZIkSZLU6q10kdsG9ATWz8yMiJOAP5Xl387MJRExHrii3PbtJeCYimtHAqeUxzXbvv1uFfshSZIkSZLU7BqdYGlo27fMvBPYrU7bD3HbN0mSJEmS1E6s6ggWSWpR3MZUkiRJUnOqdpFbSZIkSZKkds8EiyRJkiRJUpVMsEiSJEmSJFXJBIskSZIkSVKVTLBIkiRJkiRVyQSLJEmS1MpFxEYRcXdEjKqnbq+IuD8i/hoRg8uyjhFxVUTcFxHXRcTaZfnEiHgoIvqX54Mi4sw1+jKS1EqZYJEkSZJasYjoCEwCnmqgyS+AQ4BBwNiI+AxwOPBGZu4OPAOcEBG9gdeBIcBJ5bUnA5c0Yfclqc0wwSJJkiS1Ypm5lCIpMrNuXURsDbydmXMzcxHwPPBZYCBwS9nsZmAfoBswF3gJ6B4RA4GZmfl2k7+EJLUBJlgkqR1yKLkktS2ZubCBqp7AoorzbPk+vwAAHEpJREFUhWVZZXlN2Txge2BH4BXgdGBBRNwaEUObot+S1JaYYJGkdsah5JLUrnQCouI8gM51ygPonJlzKJItlwAPAo8ARwAHA6fWd/OIGB4RsyJi1sKFDeV4JKl9MMEiSe2MQ8klqV1ZQBGva3QH5tcprykjM0/LzL0o4v5FRVEuAZbVd/PMHJeZfTKzT48ePZroFSSpdTDBIkntkEPJJalti4jREXEQ8HeKJPjmEdGdImY/CkwDBpfNDyjPa67tCzyTmYuBThFRM+pFkrQCJlgkSZUcSi5JbUNPYP3MTIppnH8CJgPfLkekjAe6RsRMoDfwy4prRwJjy+NJwGxg4hrqtyS1Wh2buwOSpBblUw8lh2KxW+CbwB6ZuSQiGhxKDowD6NOnTzbFC0hSe5WZ4yuOT6w4vhPYrU7bD4GjG7jP0IrjC4ALVndfJaktcgSLJMmh5JIkSVKVGpVgiYgR5Zad0yNimzp1/zsiHii38zy8LHM7T0lqXRxKLkmSJFVhpVOEImJL4Ehgd2Bv4Hzg0LKuI/BDYCuKZM1jwHVUbOcZET+i2M7zDortPL8D/AiYTrGd5zdW7ytJkhrDoeSSJEnS6tOYESz7AH8ut/WcCuxRUbcMWEoxH78r8EFZ7naekiRJkiSp3WhMgqV2a85y6PiyiOhcni8DhgMzgCnACXWvwe08JUmSJElSG9eYBEt9W3Z2qjgfDlwG3A0cU881bucpSZIkSZLatMYkWGq35ix3huiUme+U5/8CbJqZP87MU4HtI2InVrCdZ2buRTGF6KKiKJdQTDX6hMwcl5l9MrNPjx49VvklJUmSJEmSmlJjEiz3APtGRAeKtVQeqNjO8x1g7SgB65VlbucpSZIkSZLajZXuIpSZT0fEBOA+YAnw78BZFNt5PhsRNwJ/pRiFcm1mvhAR44Eryu08X+LjqUNQbOd5Snlcs53n71bT+0iSJEmSJK1xK02wAGTmWGBsRVHldp6jgFF12rudpyRJkiRJajcaM0VIkiRJkiRJK2CCRZIkSZIkqUomWCRJkiRJkqpkgkWSJElq5SJiRETcHxHTI2KbOnX/OyIeiIi/RsThZVnHiLgqIu6LiOsiYu2yfGJEPBQR/cvzQRFx5pp/I0lqfUywSJIkSa1YRGwJHAnsCfwAOL+iriPww7LuS8CPy6rDgTcyc3fgGeCEiOgNvA4MAU4q250MXLIGXkOSWj0TLJIkSVLrtg/w58xcCkwF9qioWwYsBboDXYEPyvKBwC3l8c3lPboBc4GXgO4RMRCYmZlvN/kbSFIbYIJFkiRJat16AosAMjOBZRHRuTxfBgwHZgBTgBPqXgMsLM/nAdsDOwKvAKcDCyLi1ogYWt+DI2J4RMyKiFkLFy5sineTpFbDBIskSZLUunUCouI8yrIaw4HLgLuBY+q5JoDOmTmHItlyCfAg8AhwBHAwcGp9D87McZnZJzP79OjRY7W8jCS1Vh2buwOSJEmSqrIA2BYgIgLolJnvlOf/AmyamT8uz6dExE7lNd3K67sD8wEy87Sy3UTgm8AembkkIpatwfeRpFbJESySJElS63YPsG9EdKBYS+WBiBgdEQcB7wBrRwlYryybBgwurz+gPAcgIvoCz2TmYqBTeV3nNfc6ktQ6OYJFkiRJasUy8+mImADcBywB/h04C1g/M5+NiBuBv1IseHttZr4QEeOBKyJiJsWitsdU3HIkcEp5PAmYDfxujbyMJLViJlgkqR2KiBHANyg+iB9TzrsnIvYFzqto+s/AgUAH4DrgubL88Mx8pRxC3gs4PTOnR8QgYOfMvGDNvIkkCSAzxwJjK4pOrKgbBYyq0/5D4OgG7jW04vgCwJguSY3gFCFJamciYkvgSGBP4AfA+TV1mTklM/tlZj9gb4pdJB6gmKd/ZU1dmVzpDbwODAFOKm9xMsXiiJIkSVK7YoJFktqffYA/Z+ZSYCqwRwPtBgNTy285u/Lxdp41ugFzKYaWd4+IgcDMzHy7abotSZIktVwmWCSp/elJmSzJzASWRUR9ixceD1xVcf7NiJgREb+MiHWAecD2wI4UI11OBxZExK0RMfSTt4OIGB4RsyJi1sKFC1fjK0mSJEnNywSLJLU/nYCoOI+y7OOCiE2BLTLzYYDMvCIzdwb6AR8B3ynXbVlIMSXoQeAR4AjgYODU+h6cmeMys09m9unRo8fqfStJkiSpGTUqwRIRIyLi/oiYHhHb1KnbOCKuj4iHI+JXZVnHiLgqIu6LiOsiYu2yfGJEPBQR/cvzQRFx5up+KUnSCi2gmN5DufVmp8x8p06bY4Cr615YjniZDOxUnp+WmXsBA4GLyiZLKHaqkCRJktqNlSZYVrQYYulXwF2ZuWtmnlyWHQ68kZm7A88AJ7gYoiS1GPcA+0ZEB4r1WB6IiNERcVBFm+USLBGxSUVdf+BvFXV9gWcyczHQqUza1DflSJIkSWqzGjOCpcHFECOiC7A7cGmdawYCt5THN5f3cDFESWoBMvNpYAJwH8W2nd+mWJdlfYCI2BOYk5mvVlx2fEQ8GBEzKLZl/kVF3Ug+3hp0EjAbmNiEryBJkiS1OB0b0Wa5xRAjYllEdC6HgO8AzAcuLUeoXJmZV1ZeQzE/vyf1L4Y4KSJuBa7IzD+sxveSJK1AZo7l46QIwIkVdTOAA+u0HwOMaeBeQyuOLwAuWK2dlSRJklqBxiRYOlEsaFijZjHEJUAX4J8oFjR8E7i/TJhULqAYQOfMnBMRNYshXg9sSrEY4n7AFOATCZaIGA4MB9hqq60+7btJkiRJkiStEY2ZIrSixRAXAQ9m5vzMfA94HNi68hqgO8Uol0+9GKK7TUiSJEmSpNagMQmWFS2G+CyweUR0i4iOQG9gDjANGFxef0B5DrgYoiRJkiRJantWOkUoM5+OiJrFEJcA/w6cBayfmR9FxAiKhWw7Apdl5sKIGA9cEREzKRa1PabiliOBU8rjmsUQf7ea3keSJEltQK/v37LyRk3k+TGDV95IkqQ6GrMGy8oWQ5xOsZNQZfsPgaMbuJeLIUqSJEmSpDalMVOEJEmSJLVgETEiIu6PiOkRsU2duo0j4vqIeDgiflWWdYyIqyLivoi4LiLWLssnRsRDEdG/PB8UEWeu+TeSpNbHBIskSZLUikXElsCRwJ7AD4Dz6zT5FXBXZu6amSeXZYcDb2Tm7sAzwAkR0Rt4HRgCnFS2O5liF1BJ0ko0aoqQJEmSpBZrH+DPmbk0IqYCV9VUREQXiun8w+pcMxCYUB7fTLHG4kPAXIo1FLtHxEBgZma+3cT9l9QOtIe1tRzBIkmSJLVuPYFFAJmZwLKIqNmlcwdgPnBpRNwTEcfVvQZYWJ7PA7YHdgReAU4HFkTErRFRu45ipYgYHhGzImLWwoULm+DVJKn1MMEiSZIktW6dgKg4j7IMoAvwT8C5wFeBERHRs841AXTOzDkUyZZLgAeBR4AjgIOBU+t7cGaOy8w+mdmnR48eq/WlJKm1McEiSZIktW4LgG4AERFAp8x8p6xbBDyYmfMz8z3gcWDrymuA7hSjXMjM0zJzL4opRBcVRbkEWLamXkaSWisTLJIkSVLrdg+wb0R0oFiP5YGIGB0RBwHPAptHRLeI6Aj0BuYA04CaRQkOKM8BiIi+wDOZuRjoVCZtOiNJWiEXuZUkSZJascx8OiImAPcBS4B/p1i0dv3M/CgiRlAsZNsRuCwzF0bEeOCKiJhJsajtMRW3HAmcUh5PAmYDv1sjLyNJrZgJFkmSJKmVy8yxwNiKohMr6qZT7CRU2f5D4OgG7jW04vgC4ILV2llJaqOcIiRJkiRJklQlEyySJEmSJElVMsEiSZIkSZJUJRMsktQORcSIiLg/IqZHxDZ16qZGxMyIuDcizi3LOkbEVRFxX0RcFxFrl+UTI+KhiOhfng+KiDPX/BtJkiRJzcsEiyS1MxGxJXAksCfwA+D8Ok26Av0zs19m/rAsOxx4IzN3B54BToiI3sDrwBDgpLLdycAlTfwKkiRJUotjgkWS2p99gD9n5lJgKrBHnfqO5e4SlQYCt5THN5f36AbMpdjes3tEDARmZubbTdZzSZIkqYUywSJJ7U9PYBFAZiawLCI6V9R3joi7y5996l4DLCzP5wHbAzsCrwCnAwsi4taIGIokSZLUjjQqwbKiufoVbW6LiFHlsXP1Janl6gRExXmUZQBkZu/M3Bs4DhgfEevWuSaAzpk5hyLZcgnwIPAIcARwMHBqfQ+OiOERMSsiZi1cuHC1vpQkSZLUnFaaYGnEXH0iYhjQsaLIufqS1HItoJjeQ0QE0Ckz36nbqEygzAW2qLwG6A7ML9uclpl7UUwhuqgoyiXAsvoenJnjMrNPZvbp0aPH6n0rSZIkqRk1ZgTLCufqR0RXigTMNRXFztWXpJbrHmDfiOhAEZ8fiIjREXFQRKwdERsAREQPYBPgRWAaMLi8/oDynLJdX+CZzFwMdCqTNpVTjiRJkqQ2rzEJlpXN1f8JcB7Lf1u5WubqO5Rckla/zHwamADcB4wCvk0Rp9cvf6ZGxF8oEuSnZuYHwHiga0TMBHoDv6y45UhgbHk8CZgNTGzyF5EkSZJakI4rb0In4KOK85q5+ksi4svAu5n5YER8rs41n5irHxE1c/WvBzalmKu/HzAF+EPdB2fmOGAcQJ8+ffLTvJgkqWGZOZaPkyIAJ1Yc71ZP+w+Boxu419CK4wuAC1ZTNyVJkqRWozEJlgX8//buPcbS+q7j+PsDu2tpSy/AAgrhViwJtGoMmrKwXLdIoamUS7FoW6Rku3IVA1SjVMAYe0OLLW4gcbskFAoilHsLBct1oYVSilFcYkqCUGAhoELVDezXP84z7Nnp7M5hzsycM+d5v5IJz/k9l/P7ZdjPmXyf33N+sBtM+Kz+x4CjkxwHbAFsnmQzNvGsfnOd64CTgEVVtTbJhM/qS5IkSZIkzQW9PCK00Wf1q+oPqmrbqtqezhTzL1fV5/BZfUmSJGnWuOqnJA3epAWWSZ7V35iV+Ky+JEmSNONc9VOShkMvjwhN9qz+2DEru7Z9Vl+SJEmaHW+s+pnkDuCy7p3jVv3cqWleQucmKnS+1Pwc4BFc9VOSpqyXR4QkSZIkDS9X/ZSkIWCBRZIkSZrbulfwhPWrftK96ucmznlj1U86xZblwMPAo3RW/TwSOHWiN66qS6tq76rae+HChdM0HEmam3p6REiSJEnS0HLVT0kaAs5gkSRJkuY2V/2UpCFggUWSJEmaw1z1U5KGg48ISZIkSXOcq35K0uA5g0WSJEmSJKlPFlgkSZIkSZL6ZIFFkiRJkiSpTxZYJEmSJEmS+mSBRZIkSZIkqU8WWCRJkiRJkvpkgUWSJEmSJKlPFlgkSZIkSZL6ZIFFklooyZlJHkxyT5Jdu9oXJLkoyf1JHkmypGlfnOSZJPc2Pzs07dc1xy1uXh+e5OzBjEqSJEkaHAssktQySXYEjgf2Bc4Hvji2r6rWAt+uqkXA7wB/3ezaGvh6Ve3X/DydZA/gJeAoYFlz3MnA8tkZiSRJkjQ8eiqwTOFO57wklyVZleSqJG9p2r3TKUmDdwhwe1W9BtwBLOreWVW3NpvPAO9qtrcCXhh3na2bY54Ctmk+Ax6oqldmquOSJEnSsJq0wDLFO53HAS9X1T7AE8CnvdMpSUNjO5piSVUVsC7JggmOOxq4sev1SUnuS3Jxki2AnwK7A+8FngZOB55LckuSY2Z0BJIkSdKQ6WUGy1TudC4Bbm62b2qu4Z1OSRoO84F0vU7Ttr6hU1w/i05hnapaUVV7AfsBrwN/VFU/AdbQKZQ/DDwKfBw4Ejh1ojdOsjTJQ0keWrNmzbQOSpLazBnnkjR4vRRYpnKn841z6PzxvR1TuNPpH+KSNCOeo1P0JkmA+VX16tjOJL8AXAX8YVU9331i8zlwK7Bn8/q0qjqATmH9K80ha4F1E71xVV1aVXtX1d4LFy6c/pFJUgs541yShkMvBZY3fadz3DkBFkzlTqd/iEvSjLgbODTJ5nRmGP4gyQVJPtLsvwS4uqq+O3ZCkm27zl8M/Lhr3weAJ6rqRWB+U7SZqBAvSZoZzjiXpCHQS4FlKnc63zgH2AZ4Ft78nU5J0vSrqtXAlcAq4DzgDDozDbdsiiW/CxzbtSTznsCJSR5Och+wC/DVrkueBVzYbN8I/BC4bjbGIkkCBjjjXJK03rwejrkbWJbkXOAgmjudwENVdQMT3OkE7gKOAG4DPty8Bja805nEO52SNABVdSHriyIAn+nans/P+xfg8xu51jFd218CvjQdfZQk9Ww+ne/HGjM243ztGw3rZ5wf3HXOz804TzI24/xqYHs6M84Po/N3/TXj3zjJUmApwE477TR9I5KkOWjSGSxTvNO5EtgqyQPAHsDFXZf0TqckSZI0fQY249xH+iVpvV5msEzlTifAJzZyLe90SpIkSdPHGeeSNAR6KrBIkiRJGk5VtTrJ2IzztcCngHPYcMb57kmObU5ZSmfG+YpmxvlTwCe7LnkWcEqzPTbj/PKZHockzXUWWCRJkqQ5zhnnkjR4vawiJEmSJEmSpE2wwCJJkiRJktQnCyySJEmSJEl9ssAiSZIkSZLUJwsskiRJkiRJfbLAIkmSJEmS1CcLLJIkSZIkSX2ywCJJkiRJktQnCyySJEmSJEl9ssAiSZIkSZLUJwsskiRJkiRJfbLAIkmSJEmS1CcLLJIkSZIkSX3qqcCS5MwkDya5J8mu4/Yd0Oz7fpIjmrZ5SS5LsirJVUne0rRfl+SRJIub14cnOXu6ByVJ2jRzXZJGi7kuSYM3aYElyY7A8cC+wPnAF8cd8lXgo8DhwIVJNgOOA16uqn2AJ4BPJ9kDeAk4CljWnHsysHwaxiFJ6pG5LkmjxVyXpOHQywyWQ4Dbq+o14A5g0diOJDsDr1TVM1X1AvAk8D5gCXBzc9hNzTW2Bp4BngK2SbIEeKCqXpmmsUiSemOuS9JoMdclaQj0UmDZDngBoKoKWJdkwfh9jTV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      "text/plain": [
       "<Figure size 1368x648 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 因子分组平均收益\n",
    "fig, axes = plt.subplots(2, 3, figsize=(19, 9))\n",
    "axes = [i for x in axes for i in x]\n",
    "for ax, (k, v) in zip(axes, res_dic.items()):\n",
    "    \n",
    "    mono_score = calc_mono_score(v.group_returns)\n",
    "    ax.yaxis.set_major_formatter(\n",
    "        mpl.ticker.FuncFormatter(lambda x, pos: '%.2f%%' % (x * 100)))\n",
    "    ax.text(0.65,0.95,\"单调性得分为:%.3f\"%mono_score,\n",
    "           fontsize=10,\n",
    "           bbox={'facecolor': 'white', 'alpha': 1, 'pad': 5},\n",
    "           transform=ax.transAxes,\n",
    "           verticalalignment='top')\n",
    "    v.group_returns.mean().plot.bar(ax=ax, title=k, color='#1f77b4')\n",
    "\n",
    "plt.subplots_adjust(hspace=0.5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "由于 A股市场中做空手段相对有限,所以我们将重心放在多头组的分析中,从上图中可以看到第一组的收益相对较好，分别查看第一组每年的收益情况:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "code_folding": [
     0
    ]
   },
   "outputs": [
    {
     "data": {
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       "             height:  80%;\n",
       "            background:  linear-gradient(90deg, transparent 0%, transparent 34.7%, #d65f5f 34.7%, #d65f5f 68.1%, transparent 68.1%);\n",
       "        }    #T_02c04bbc_6870_11ec_9179_0ae072946bf2row2_col4 {\n",
       "            width:  10em;\n",
       "             height:  80%;\n",
       "            background:  linear-gradient(90deg, transparent 0%, transparent 30.1%, #d65f5f 30.1%, #d65f5f 69.8%, transparent 69.8%);\n",
       "        }    #T_02c04bbc_6870_11ec_9179_0ae072946bf2row2_col5 {\n",
       "            width:  10em;\n",
       "             height:  80%;\n",
       "            background:  linear-gradient(90deg, transparent 0%, transparent 30.4%, #d65f5f 30.4%, #d65f5f 69.7%, transparent 69.7%);\n",
       "        }    #T_02c04bbc_6870_11ec_9179_0ae072946bf2row3_col0 {\n",
       "            width:  10em;\n",
       "             height:  80%;\n",
       "            background:  linear-gradient(90deg, transparent 0%, transparent 16.0%, #5fba7d 16.0%, #5fba7d 29.4%, transparent 29.4%);\n",
       "        }    #T_02c04bbc_6870_11ec_9179_0ae072946bf2row3_col1 {\n",
       "            width:  10em;\n",
       "             height:  80%;\n",
       "            background:  linear-gradient(90deg, transparent 0%, transparent 15.0%, #5fba7d 15.0%, #5fba7d 25.0%, transparent 25.0%);\n",
       "        }    #T_02c04bbc_6870_11ec_9179_0ae072946bf2row3_col2 {\n",
       "            width:  10em;\n",
       "             height:  80%;\n",
       "            background:  linear-gradient(90deg, transparent 0%, transparent 15.0%, #5fba7d 15.0%, #5fba7d 24.7%, transparent 24.7%);\n",
       "        }    #T_02c04bbc_6870_11ec_9179_0ae072946bf2row3_col3 {\n",
       "            width:  10em;\n",
       "             height:  80%;\n",
       "            background:  linear-gradient(90deg, transparent 0%, transparent 17.6%, #5fba7d 17.6%, #5fba7d 34.7%, transparent 34.7%);\n",
       "        }    #T_02c04bbc_6870_11ec_9179_0ae072946bf2row3_col4 {\n",
       "            width:  10em;\n",
       "             height:  80%;\n",
       "            background:  linear-gradient(90deg, transparent 0%, transparent 14.9%, #5fba7d 14.9%, #5fba7d 30.1%, transparent 30.1%);\n",
       "        }    #T_02c04bbc_6870_11ec_9179_0ae072946bf2row3_col5 {\n",
       "            width:  10em;\n",
       "             height:  80%;\n",
       "            background:  linear-gradient(90deg, transparent 0%, transparent 16.6%, #5fba7d 16.6%, #5fba7d 30.4%, transparent 30.4%);\n",
       "        }    #T_02c04bbc_6870_11ec_9179_0ae072946bf2row4_col0 {\n",
       "            width:  10em;\n",
       "             height:  80%;\n",
       "            background:  linear-gradient(90deg, transparent 0%, transparent -0.0%, #5fba7d -0.0%, #5fba7d 29.4%, transparent 29.4%);\n",
       "        }    #T_02c04bbc_6870_11ec_9179_0ae072946bf2row4_col1 {\n",
       "            width:  10em;\n",
       "             height:  80%;\n",
       "            background:  linear-gradient(90deg, transparent 0%, transparent -0.0%, #5fba7d -0.0%, #5fba7d 25.0%, transparent 25.0%);\n",
       "        }    #T_02c04bbc_6870_11ec_9179_0ae072946bf2row4_col2 {\n",
       "            width:  10em;\n",
       "             height:  80%;\n",
       "            background:  linear-gradient(90deg, transparent 0%, transparent 0.0%, #5fba7d 0.0%, #5fba7d 24.7%, transparent 24.7%);\n",
       "        }    #T_02c04bbc_6870_11ec_9179_0ae072946bf2row4_col3 {\n",
       "            width:  10em;\n",
       "             height:  80%;\n",
       "            background:  linear-gradient(90deg, transparent 0%, transparent 0.0%, #5fba7d 0.0%, #5fba7d 34.7%, transparent 34.7%);\n",
       "        }    #T_02c04bbc_6870_11ec_9179_0ae072946bf2row4_col4 {\n",
       "            width:  10em;\n",
       "             height:  80%;\n",
       "            background:  linear-gradient(90deg, transparent 0%, transparent 0.0%, #5fba7d 0.0%, #5fba7d 30.1%, transparent 30.1%);\n",
       "        }    #T_02c04bbc_6870_11ec_9179_0ae072946bf2row4_col5 {\n",
       "            width:  10em;\n",
       "             height:  80%;\n",
       "            background:  linear-gradient(90deg, transparent 0%, transparent 0.0%, #5fba7d 0.0%, #5fba7d 30.4%, transparent 30.4%);\n",
       "        }    #T_02c04bbc_6870_11ec_9179_0ae072946bf2row5_col0 {\n",
       "            width:  10em;\n",
       "             height:  80%;\n",
       "            background:  linear-gradient(90deg, transparent 0%, transparent 29.4%, #d65f5f 29.4%, #d65f5f 69.8%, transparent 69.8%);\n",
       "        }    #T_02c04bbc_6870_11ec_9179_0ae072946bf2row5_col1 {\n",
       "            width:  10em;\n",
       "             height:  80%;\n",
       "            background:  linear-gradient(90deg, transparent 0%, transparent 25.0%, #d65f5f 25.0%, #d65f5f 56.0%, transparent 56.0%);\n",
       "        }    #T_02c04bbc_6870_11ec_9179_0ae072946bf2row5_col2 {\n",
       "            width:  10em;\n",
       "             height:  80%;\n",
       "            background:  linear-gradient(90deg, transparent 0%, transparent 24.7%, #d65f5f 24.7%, #d65f5f 60.5%, transparent 60.5%);\n",
       "        }    #T_02c04bbc_6870_11ec_9179_0ae072946bf2row5_col3 {\n",
       "            width:  10em;\n",
       "             height:  80%;\n",
       "            background:  linear-gradient(90deg, transparent 0%, transparent 34.7%, #d65f5f 34.7%, #d65f5f 79.8%, transparent 79.8%);\n",
       "        }    #T_02c04bbc_6870_11ec_9179_0ae072946bf2row5_col4 {\n",
       "            width:  10em;\n",
       "             height:  80%;\n",
       "            background:  linear-gradient(90deg, transparent 0%, transparent 30.1%, #d65f5f 30.1%, #d65f5f 67.2%, transparent 67.2%);\n",
       "        }    #T_02c04bbc_6870_11ec_9179_0ae072946bf2row5_col5 {\n",
       "            width:  10em;\n",
       "             height:  80%;\n",
       "            background:  linear-gradient(90deg, transparent 0%, transparent 30.4%, #d65f5f 30.4%, #d65f5f 68.8%, transparent 68.8%);\n",
       "        }    #T_02c04bbc_6870_11ec_9179_0ae072946bf2row6_col0 {\n",
       "            width:  10em;\n",
       "             height:  80%;\n",
       "            background:  linear-gradient(90deg, transparent 0%, transparent 29.4%, #d65f5f 29.4%, #d65f5f 40.4%, transparent 40.4%);\n",
       "        }    #T_02c04bbc_6870_11ec_9179_0ae072946bf2row6_col1 {\n",
       "            width:  10em;\n",
       "             height:  80%;\n",
       "            background:  linear-gradient(90deg, transparent 0%, transparent 25.0%, #d65f5f 25.0%, #d65f5f 38.3%, transparent 38.3%);\n",
       "        }    #T_02c04bbc_6870_11ec_9179_0ae072946bf2row6_col2 {\n",
       "            width:  10em;\n",
       "             height:  80%;\n",
       "            background:  linear-gradient(90deg, transparent 0%, transparent 24.7%, #d65f5f 24.7%, #d65f5f 38.7%, transparent 38.7%);\n",
       "        }    #T_02c04bbc_6870_11ec_9179_0ae072946bf2row6_col3 {\n",
       "            width:  10em;\n",
       "             height:  80%;\n",
       "            background:  linear-gradient(90deg, transparent 0%, transparent 34.7%, #d65f5f 34.7%, #d65f5f 41.0%, transparent 41.0%);\n",
       "        }    #T_02c04bbc_6870_11ec_9179_0ae072946bf2row6_col4 {\n",
       "            width:  10em;\n",
       "             height:  80%;\n",
       "            background:  linear-gradient(90deg, transparent 0%, transparent 30.1%, #d65f5f 30.1%, #d65f5f 43.1%, transparent 43.1%);\n",
       "        }    #T_02c04bbc_6870_11ec_9179_0ae072946bf2row6_col5 {\n",
       "            width:  10em;\n",
       "             height:  80%;\n",
       "            background:  linear-gradient(90deg, transparent 0%, transparent 30.4%, #d65f5f 30.4%, #d65f5f 39.9%, transparent 39.9%);\n",
       "        }    #T_02c04bbc_6870_11ec_9179_0ae072946bf2row7_col0 {\n",
       "            width:  10em;\n",
       "             height:  80%;\n",
       "            background:  linear-gradient(90deg, transparent 0%, transparent 29.4%, #d65f5f 29.4%, #d65f5f 61.6%, transparent 61.6%);\n",
       "        }    #T_02c04bbc_6870_11ec_9179_0ae072946bf2row7_col1 {\n",
       "            width:  10em;\n",
       "             height:  80%;\n",
       "            background:  linear-gradient(90deg, transparent 0%, transparent 25.0%, #d65f5f 25.0%, #d65f5f 63.7%, transparent 63.7%);\n",
       "        }    #T_02c04bbc_6870_11ec_9179_0ae072946bf2row7_col2 {\n",
       "            width:  10em;\n",
       "             height:  80%;\n",
       "            background:  linear-gradient(90deg, transparent 0%, transparent 24.7%, #d65f5f 24.7%, #d65f5f 61.7%, transparent 61.7%);\n",
       "        }    #T_02c04bbc_6870_11ec_9179_0ae072946bf2row7_col3 {\n",
       "            width:  10em;\n",
       "             height:  80%;\n",
       "            background:  linear-gradient(90deg, transparent 0%, transparent 34.7%, #d65f5f 34.7%, #d65f5f 63.8%, transparent 63.8%);\n",
       "        }    #T_02c04bbc_6870_11ec_9179_0ae072946bf2row7_col4 {\n",
       "            width:  10em;\n",
       "             height:  80%;\n",
       "            background:  linear-gradient(90deg, transparent 0%, transparent 30.1%, #d65f5f 30.1%, #d65f5f 66.2%, transparent 66.2%);\n",
       "        }    #T_02c04bbc_6870_11ec_9179_0ae072946bf2row7_col5 {\n",
       "            width:  10em;\n",
       "             height:  80%;\n",
       "            background:  linear-gradient(90deg, transparent 0%, transparent 30.4%, #d65f5f 30.4%, #d65f5f 60.0%, transparent 60.0%);\n",
       "        }</style>  \n",
       "<table id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2\" > \n",
       "<thead>    <tr> \n",
       "        <th class=\"blank level0\" ></th> \n",
       "        <th class=\"col_heading level0 col0\" >pv_corr_avg</th> \n",
       "        <th class=\"col_heading level0 col1\" >pv_corr_std</th> \n",
       "        <th class=\"col_heading level0 col2\" >pv_corr</th> \n",
       "        <th class=\"col_heading level0 col3\" >pv_corr_trend</th> \n",
       "        <th class=\"col_heading level0 col4\" >pv_corr_deret20</th> \n",
       "        <th class=\"col_heading level0 col5\" >CPV</th> \n",
       "    </tr>    <tr> \n",
       "        <th class=\"index_name level0\" >年度</th> \n",
       "        <th class=\"blank\" ></th> \n",
       "        <th class=\"blank\" ></th> \n",
       "        <th class=\"blank\" ></th> \n",
       "        <th class=\"blank\" ></th> \n",
       "        <th class=\"blank\" ></th> \n",
       "        <th class=\"blank\" ></th> \n",
       "    </tr></thead> \n",
       "<tbody>    <tr> \n",
       "        <th id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2level0_row0\" class=\"row_heading level0 row0\" >2014</th> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row0_col0\" class=\"data row0 col0\" >53.73%</td> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row0_col1\" class=\"data row0 col1\" >68.62%</td> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row0_col2\" class=\"data row0 col2\" >65.39%</td> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row0_col3\" class=\"data row0 col3\" >55.99%</td> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row0_col4\" class=\"data row0 col4\" >57.22%</td> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row0_col5\" class=\"data row0 col5\" >59.41%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2level0_row1\" class=\"row_heading level0 row1\" >2015</th> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row1_col0\" class=\"data row1 col0\" >19.73%</td> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row1_col1\" class=\"data row1 col1\" >37.41%</td> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row1_col2\" class=\"data row1 col2\" >34.34%</td> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row1_col3\" class=\"data row1 col3\" >19.30%</td> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row1_col4\" class=\"data row1 col4\" >41.24%</td> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row1_col5\" class=\"data row1 col5\" >37.34%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2level0_row2\" class=\"row_heading level0 row2\" >2016</th> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row2_col0\" class=\"data row2 col0\" >30.70%</td> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row2_col1\" class=\"data row2 col1\" >35.17%</td> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row2_col2\" class=\"data row2 col2\" >34.28%</td> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row2_col3\" class=\"data row2 col3\" >28.65%</td> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row2_col4\" class=\"data row2 col4\" >32.54%</td> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row2_col5\" class=\"data row2 col5\" >33.58%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2level0_row3\" class=\"row_heading level0 row3\" >2017</th> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row3_col0\" class=\"data row3 col0\" >-10.25%</td> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row3_col1\" class=\"data row3 col1\" >-9.13%</td> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row3_col2\" class=\"data row3 col2\" >-8.39%</td> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row3_col3\" class=\"data row3 col3\" >-14.62%</td> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row3_col4\" class=\"data row3 col4\" >-12.38%</td> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row3_col5\" class=\"data row3 col5\" >-11.76%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2level0_row4\" class=\"row_heading level0 row4\" >2018</th> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row4_col0\" class=\"data row4 col0\" >-22.41%</td> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row4_col1\" class=\"data row4 col1\" >-22.85%</td> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row4_col2\" class=\"data row4 col2\" >-21.41%</td> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row4_col3\" class=\"data row4 col3\" >-29.72%</td> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row4_col4\" class=\"data row4 col4\" >-24.58%</td> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row4_col5\" class=\"data row4 col5\" >-25.94%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2level0_row5\" class=\"row_heading level0 row5\" >2019</th> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row5_col0\" class=\"data row5 col0\" >30.71%</td> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row5_col1\" class=\"data row5 col1\" >28.41%</td> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row5_col2\" class=\"data row5 col2\" >31.11%</td> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row5_col3\" class=\"data row5 col3\" >38.70%</td> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row5_col4\" class=\"data row5 col4\" >30.40%</td> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row5_col5\" class=\"data row5 col5\" >32.82%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2level0_row6\" class=\"row_heading level0 row6\" >2020</th> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row6_col0\" class=\"data row6 col0\" >8.34%</td> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row6_col1\" class=\"data row6 col1\" >12.23%</td> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row6_col2\" class=\"data row6 col2\" >12.18%</td> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row6_col3\" class=\"data row6 col3\" >5.41%</td> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row6_col4\" class=\"data row6 col4\" >10.65%</td> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row6_col5\" class=\"data row6 col5\" >8.14%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2level0_row7\" class=\"row_heading level0 row7\" >2021</th> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row7_col0\" class=\"data row7 col0\" >24.46%</td> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row7_col1\" class=\"data row7 col1\" >35.39%</td> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row7_col2\" class=\"data row7 col2\" >32.15%</td> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row7_col3\" class=\"data row7 col3\" >24.95%</td> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row7_col4\" class=\"data row7 col4\" >29.57%</td> \n",
       "        <td id=\"T_02c04bbc_6870_11ec_9179_0ae072946bf2row7_col5\" class=\"data row7 col5\" >25.27%</td> \n",
       "    </tr></tbody> \n",
       "</table> "
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7fd6c42888d0>"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# report\n",
    "ret_by_y = pd.DataFrame(columns=list(res_dic.keys()))\n",
    "ic_df = pd.DataFrame(columns=list(res_dic.keys()))\n",
    "risk_df = pd.DataFrame(columns=list(res_dic.keys()))\n",
    "for k, v in res_dic.items():\n",
    "\n",
    "    ret_by_y[k] = v.group_returns[1].groupby(pd.Grouper(\n",
    "        level=0, freq='Y')).apply(lambda x: ep.cum_returns(x)[-1])\n",
    "\n",
    "    ic_df[k] = get_information_table(\n",
    "        perf.factor_information_coefficient(v.factors_frame)).iloc[:, 0]\n",
    "    risk_df[k] = get_performance_table(v.group_returns[[1]],\n",
    "                                       periods='monthly').iloc[:, 0]\n",
    "\n",
    "ret_by_y.index = ret_by_y.index.strftime('%Y')\n",
    "ret_by_y.index.names = ['年度']\n",
    "\n",
    "ret_by_y.style.format('{:.2%}').bar(align='mid', color=['#5fba7d', '#d65f5f'])"
   ]
  },
  {
   "cell_type": "code",
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    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "    #T_3ea3b9f2_6870_11ec_9179_0ae072946bf2row0_col1 {\n",
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       "            background-color:  #d65f5f;\n",
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       "            background-color:  #d65f5f;\n",
       "        }</style>  \n",
       "<table id=\"T_3ea3b9f2_6870_11ec_9179_0ae072946bf2\" > \n",
       "<thead>    <tr> \n",
       "        <th class=\"blank level0\" ></th> \n",
       "        <th class=\"col_heading level0 col0\" >pv_corr_avg</th> \n",
       "        <th class=\"col_heading level0 col1\" >pv_corr_std</th> \n",
       "        <th class=\"col_heading level0 col2\" >pv_corr</th> \n",
       "        <th class=\"col_heading level0 col3\" >pv_corr_trend</th> \n",
       "        <th class=\"col_heading level0 col4\" >pv_corr_deret20</th> \n",
       "        <th class=\"col_heading level0 col5\" >CPV</th> \n",
       "    </tr></thead> \n",
       "<tbody>    <tr> \n",
       "        <th id=\"T_3ea3b9f2_6870_11ec_9179_0ae072946bf2level0_row0\" class=\"row_heading level0 row0\" >年化收益率</th> \n",
       "        <td id=\"T_3ea3b9f2_6870_11ec_9179_0ae072946bf2row0_col0\" class=\"data row0 col0\" >14.82%</td> \n",
       "        <td id=\"T_3ea3b9f2_6870_11ec_9179_0ae072946bf2row0_col1\" class=\"data row0 col1\" >20.41%</td> \n",
       "        <td id=\"T_3ea3b9f2_6870_11ec_9179_0ae072946bf2row0_col2\" class=\"data row0 col2\" >20.01%</td> \n",
       "        <td id=\"T_3ea3b9f2_6870_11ec_9179_0ae072946bf2row0_col3\" class=\"data row0 col3\" >13.11%</td> \n",
       "        <td id=\"T_3ea3b9f2_6870_11ec_9179_0ae072946bf2row0_col4\" class=\"data row0 col4\" >17.91%</td> \n",
       "        <td id=\"T_3ea3b9f2_6870_11ec_9179_0ae072946bf2row0_col5\" class=\"data row0 col5\" >17.08%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_3ea3b9f2_6870_11ec_9179_0ae072946bf2level0_row1\" class=\"row_heading level0 row1\" >累计收益</th> \n",
       "        <td id=\"T_3ea3b9f2_6870_11ec_9179_0ae072946bf2row1_col0\" class=\"data row1 col0\" >195.24%</td> \n",
       "        <td id=\"T_3ea3b9f2_6870_11ec_9179_0ae072946bf2row1_col1\" class=\"data row1 col1\" >328.40%</td> \n",
       "        <td id=\"T_3ea3b9f2_6870_11ec_9179_0ae072946bf2row1_col2\" class=\"data row1 col2\" >317.44%</td> \n",
       "        <td id=\"T_3ea3b9f2_6870_11ec_9179_0ae072946bf2row1_col3\" class=\"data row1 col3\" >162.43%</td> \n",
       "        <td id=\"T_3ea3b9f2_6870_11ec_9179_0ae072946bf2row1_col4\" class=\"data row1 col4\" >263.53%</td> \n",
       "        <td id=\"T_3ea3b9f2_6870_11ec_9179_0ae072946bf2row1_col5\" class=\"data row1 col5\" >243.90%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_3ea3b9f2_6870_11ec_9179_0ae072946bf2level0_row2\" class=\"row_heading level0 row2\" >波动率</th> \n",
       "        <td id=\"T_3ea3b9f2_6870_11ec_9179_0ae072946bf2row2_col0\" class=\"data row2 col0\" >29.51%</td> \n",
       "        <td id=\"T_3ea3b9f2_6870_11ec_9179_0ae072946bf2row2_col1\" class=\"data row2 col1\" >28.45%</td> \n",
       "        <td id=\"T_3ea3b9f2_6870_11ec_9179_0ae072946bf2row2_col2\" class=\"data row2 col2\" >29.27%</td> \n",
       "        <td id=\"T_3ea3b9f2_6870_11ec_9179_0ae072946bf2row2_col3\" class=\"data row2 col3\" >28.22%</td> \n",
       "        <td id=\"T_3ea3b9f2_6870_11ec_9179_0ae072946bf2row2_col4\" class=\"data row2 col4\" >30.25%</td> \n",
       "        <td id=\"T_3ea3b9f2_6870_11ec_9179_0ae072946bf2row2_col5\" class=\"data row2 col5\" >29.53%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_3ea3b9f2_6870_11ec_9179_0ae072946bf2level0_row3\" class=\"row_heading level0 row3\" >夏普</th> \n",
       "        <td id=\"T_3ea3b9f2_6870_11ec_9179_0ae072946bf2row3_col0\" class=\"data row3 col0\" >61.59%</td> \n",
       "        <td id=\"T_3ea3b9f2_6870_11ec_9179_0ae072946bf2row3_col1\" class=\"data row3 col1\" >79.62%</td> \n",
       "        <td id=\"T_3ea3b9f2_6870_11ec_9179_0ae072946bf2row3_col2\" class=\"data row3 col2\" >77.07%</td> \n",
       "        <td id=\"T_3ea3b9f2_6870_11ec_9179_0ae072946bf2row3_col3\" class=\"data row3 col3\" >57.74%</td> \n",
       "        <td id=\"T_3ea3b9f2_6870_11ec_9179_0ae072946bf2row3_col4\" class=\"data row3 col4\" >69.47%</td> \n",
       "        <td id=\"T_3ea3b9f2_6870_11ec_9179_0ae072946bf2row3_col5\" class=\"data row3 col5\" >68.08%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_3ea3b9f2_6870_11ec_9179_0ae072946bf2level0_row4\" class=\"row_heading level0 row4\" >最大回撤</th> \n",
       "        <td id=\"T_3ea3b9f2_6870_11ec_9179_0ae072946bf2row4_col0\" class=\"data row4 col0\" >-44.81%</td> \n",
       "        <td id=\"T_3ea3b9f2_6870_11ec_9179_0ae072946bf2row4_col1\" class=\"data row4 col1\" >-36.93%</td> \n",
       "        <td id=\"T_3ea3b9f2_6870_11ec_9179_0ae072946bf2row4_col2\" class=\"data row4 col2\" >-38.73%</td> \n",
       "        <td id=\"T_3ea3b9f2_6870_11ec_9179_0ae072946bf2row4_col3\" class=\"data row4 col3\" >-50.95%</td> \n",
       "        <td id=\"T_3ea3b9f2_6870_11ec_9179_0ae072946bf2row4_col4\" class=\"data row4 col4\" >-41.85%</td> \n",
       "        <td id=\"T_3ea3b9f2_6870_11ec_9179_0ae072946bf2row4_col5\" class=\"data row4 col5\" >-42.17%</td> \n",
       "    </tr></tbody> \n",
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       "<pandas.io.formats.style.Styler at 0x7fd6b33c9630>"
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   "source": [
    "risk_df.style.format('{:.2%}').highlight_max(axis=1, color='#d65f5f')"
   ]
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   "execution_count": 55,
   "metadata": {},
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    {
     "data": {
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       "<div>\n",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>pv_corr_avg</th>\n",
       "      <th>pv_corr_std</th>\n",
       "      <th>pv_corr</th>\n",
       "      <th>pv_corr_trend</th>\n",
       "      <th>pv_corr_deret20</th>\n",
       "      <th>CPV</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>IC Mean</th>\n",
       "      <td>-0.046</td>\n",
       "      <td>-0.069</td>\n",
       "      <td>-0.076</td>\n",
       "      <td>-0.018</td>\n",
       "      <td>-0.050</td>\n",
       "      <td>-0.048</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IC Std.</th>\n",
       "      <td>0.068</td>\n",
       "      <td>0.076</td>\n",
       "      <td>0.068</td>\n",
       "      <td>0.042</td>\n",
       "      <td>0.054</td>\n",
       "      <td>0.050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Risk-Adjusted IC</th>\n",
       "      <td>-0.680</td>\n",
       "      <td>-0.908</td>\n",
       "      <td>-1.113</td>\n",
       "      <td>-0.431</td>\n",
       "      <td>-0.918</td>\n",
       "      <td>-0.957</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>t-stat(IC)</th>\n",
       "      <td>-6.589</td>\n",
       "      <td>-8.800</td>\n",
       "      <td>-10.794</td>\n",
       "      <td>-4.180</td>\n",
       "      <td>-8.905</td>\n",
       "      <td>-9.274</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>p-value(IC)</th>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IC Skew</th>\n",
       "      <td>-0.491</td>\n",
       "      <td>0.437</td>\n",
       "      <td>0.267</td>\n",
       "      <td>0.114</td>\n",
       "      <td>-0.169</td>\n",
       "      <td>0.405</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IC Kurtosis</th>\n",
       "      <td>1.192</td>\n",
       "      <td>0.667</td>\n",
       "      <td>0.008</td>\n",
       "      <td>0.216</td>\n",
       "      <td>0.782</td>\n",
       "      <td>0.333</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  pv_corr_avg  pv_corr_std  ...    pv_corr_deret20    CPV\n",
       "IC Mean                -0.046       -0.069  ...             -0.050 -0.048\n",
       "IC Std.                 0.068        0.076  ...              0.054  0.050\n",
       "Risk-Adjusted IC       -0.680       -0.908  ...             -0.918 -0.957\n",
       "t-stat(IC)             -6.589       -8.800  ...             -8.905 -9.274\n",
       "p-value(IC)             0.000        0.000  ...              0.000  0.000\n",
       "IC Skew                -0.491        0.437  ...             -0.169  0.405\n",
       "IC Kurtosis             1.192        0.667  ...              0.782  0.333\n",
       "\n",
       "[7 rows x 6 columns]"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# IC统计\n",
    "ic_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 总结\n",
    "\n",
    "本篇报告从技术分析中最简单的价量关系入手，在计算股票每日高频价量相关系数 的基础上，逐步挖掘了其中蕴藏的选股因子。\n",
    "\n",
    "首先，我们定义了价量相关性的**平均数因子**和**波动性因子**。研究发现，两者其实都可以看做是对传统反转因子的修正。平均数因子认为，股票的月度行情是否反转需要看成交量的信息，若有量的确认，则月度行情的反转效应更强；而若没有量的确认，则月度行情更容易呈现动量效应。波动性因子则不论股票过去价格的涨跌，只要每日价量关 系维持稳定形态，下个月就更有可能上涨；而价量关系在多种形态间频繁转换的股票，下个月更有可能下跌。\n",
    "\n",
    "其次，我们发现股票价量相关性的变化趋势也具有不错的选股能力，因此定义了**趋势因子**。回测结果显示，上个月的趋势因子值越小，即价量相关系数随时间推移逐渐变小的股票，下个月的收益倾向于越高，这与平均数因子的选股逻辑相呼应。\n",
    "\n",
    "最后，本篇报告综合上述3个维度的信息，构建了最终的**价量相关性因子CPV**，其各项回测指标均大幅优于传统反转因子。即使剔除市场常用风格和行业的干扰，纯净CPV 因子仍然具备良好的选股能力。"
   ]
  }
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